Probability Definitions

Question Types
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Exercise 1 (5 points) -- Common to all candidates
In this exercise, probabilities should be rounded to the nearest hundredth.
Part A
A wholesaler buys boxes of green tea from two suppliers. He buys 80\% of his boxes from supplier A and 20\% from supplier B. 10\% of the boxes from supplier A show traces of pesticides and 20\% of those from supplier B also show traces of pesticides.
A box is randomly selected from the wholesaler's stock and the following events are considered: --- event $A$: ``the box comes from supplier A''; --- event $B$: ``the box comes from supplier B''; --- event $S$: ``the box shows traces of pesticides''.
  1. Translate the statement in the form of a weighted tree diagram.
  2. a. What is the probability of event $B \cap \bar{S}$? b. Justify that the probability that the selected box shows no traces of pesticides is equal to 0.88.
  3. It is observed that the selected box shows traces of pesticides. What is the probability that this box comes from supplier B?

Part B
The manager of a tea salon buys 10 boxes from the above wholesaler. It is assumed that the latter's stock is sufficiently large to model this situation by random selection of 10 boxes with replacement. Consider the random variable $X$ which associates with this sample of 10 boxes the number of boxes without traces of pesticides.
  1. Justify that the random variable $X$ follows a binomial distribution and specify its parameters.
  2. Calculate the probability that all 10 boxes are free of pesticide traces.
  3. Calculate the probability that at least 8 boxes show no traces of pesticides.

Part C
For advertising purposes, the wholesaler displays on his leaflets: ``88\% of our tea is guaranteed free of pesticide traces''.
An inspector from the fraud prevention unit wishes to study the validity of this claim. To this end, he randomly selects 50 boxes from the wholesaler's stock and finds 12 with traces of pesticides.
It is assumed that in the wholesaler's stock, the proportion of boxes without traces of pesticides is indeed equal to 0.88. Let $F$ be the random variable which, for any sample of 50 boxes, associates the frequency of boxes containing no traces of pesticides.
  1. Give the asymptotic confidence interval for the random variable $F$ at the 95\% confidence level.
  2. Can the fraud prevention inspector decide, at the 95\% confidence level, that the advertisement is misleading?
A garden centre sells young tree saplings that come from three horticulturists: $35 \%$ of the plants come from horticulturist $\mathrm { H } _ { 1 } , 25 \%$ from horticulturist $\mathrm { H } _ { 2 }$ and the rest from horticulturist $\mathrm { H } _ { 3 }$. Each horticulturist supplies two categories of trees: conifers and deciduous trees. The delivery from horticulturist $\mathrm { H } _ { 1 }$ contains $80 \%$ conifers while that from horticulturist $\mathrm { H } _ { 2 }$ contains only $50 \%$ and that from horticulturist $\mathrm { H } _ { 3 }$ only $30 \%$.
We consider the following events: $H _ { 1 }$ : ``the tree chosen was purchased from horticulturist $\mathrm { H } _ { 1 }$'', $H _ { 2 }$ : ``the tree chosen was purchased from horticulturist $\mathrm { H } _ { 2 }$'', $H _ { 3 }$ : ``the tree chosen was purchased from horticulturist $\mathrm { H } _ { 3 }$'', $C$ : ``the tree chosen is a conifer'', $F$ : ``the tree chosen is a deciduous tree''.
  1. The garden centre manager chooses a tree at random from his stock.
    1. [a.] Construct a probability tree representing the situation.
    2. [b.] Calculate the probability that the tree chosen is a conifer purchased from horticulturist $\mathrm { H } _ { 3 }$.
    3. [c.] Justify that the probability of event $C$ is equal to 0.525.
    4. [d.] The tree chosen is a conifer. What is the probability that it was purchased from horticulturist $\mathrm { H } _ { 1 }$? Round to $10 ^ { - 3 }$.
  2. A random sample of 10 trees is chosen from the stock of this garden centre. We assume that this stock is large enough that this choice can be treated as sampling with replacement of 10 trees from the stock. Let $X$ be the random variable that gives the number of conifers in the chosen sample.
    1. [a.] Justify that $X$ follows a binomial distribution and specify its parameters.
    2. [b.] What is the probability that the sample contains exactly 5 conifers? Round to $10 ^ { - 3 }$.
    3. [c.] What is the probability that this sample contains at least two deciduous trees? Round to $10 ^ { - 3 }$.
In a factory, two machines A and B are used to manufacture parts.
Machine A ensures $40\%$ of production and machine B ensures $60\%$. It is estimated that $10\%$ of parts from machine A have a defect and that $9\%$ of parts from machine B have a defect.
A part is chosen at random and we consider the following events:
  • $A$: ``The part is produced by machine A''
  • $B$: ``The part is produced by machine B''
  • $D$: ``The part has a defect''
  • $\bar{D}$: the opposite event of event $D$.

  1. a. Translate the situation using a probability tree. b. Calculate the probability that the chosen part has a defect and was manufactured by machine A. c. Prove that the probability $P(D)$ of event $D$ is equal to 0.094. d. It is observed that the chosen part has a defect. What is the probability that this part comes from machine A?
  2. It is estimated that machine A is properly adjusted if $90\%$ of the parts it manufactures are conforming. It is decided to check this machine by examining $n$ parts chosen at random ($n$ natural integer) from the production of machine A. These $n$ draws are treated as successive independent draws with replacement. We denote by $X_n$ the number of parts that are conforming in the sample of $n$ parts, and $F_n = \dfrac{X_n}{n}$ the corresponding proportion. a. Justify that the random variable $X_n$ follows a binomial distribution and specify its parameters. b. In this question, we take $n = 150$. Determine the asymptotic fluctuation interval $I$ at the $95\%$ threshold of the random variable $F_{150}$. c. A quality test counts 21 non-conforming parts in a sample of 150 parts produced. Does this call into question the adjustment of the machine? Justify the answer.
The company produces $40 \%$ of small-sized footballs and $60 \%$ of standard-sized footballs. It is admitted that $2 \%$ of small-sized footballs and $5 \%$ of standard-sized footballs do not comply with regulations. A football is chosen at random in the company.
Consider the events: $A$ : ``the football is small-sized'', $B$ : ``the football is standard-sized'', $C$ : ``the football complies with regulations'' and $\bar { C }$, the opposite event of C.
  1. Represent this random experiment using a probability tree.
  2. Calculate the probability that the football is small-sized and complies with regulations.
  3. Show that the probability of event $C$ is equal to 0.962.
  4. The football chosen does not comply with regulations. What is the probability that this football is small-sized? Round the result to $10 ^ { - 3 }$.
Exercise 1 (5 points)
Part A
An oyster farmer raises two species of oysters: ``the flat'' and ``the Japanese''. Each year, flat oysters represent $15 \%$ of his production. Oysters are said to be of size $\mathrm { n } ^ { \circ } 3$ when their mass is between 66 g and 85 g. Only $10 \%$ of flat oysters are of size $\mathrm { n } ^ { \circ } 3$, whereas $80 \%$ of Japanese oysters are.
  1. The health service randomly selects an oyster from the oyster farmer's production. We assume that all oysters have an equal chance of being selected. We consider the following events:
    • J: ``the selected oyster is a Japanese oyster'',
    • C: ``the selected oyster is of size $\mathrm { n } ^ { \circ } 3$''.
    a. Construct a complete weighted tree representing the situation. b. Calculate the probability that the selected oyster is a flat oyster of size $\mathrm { n } ^ { \mathrm { o } } 3$. c. Justify that the probability of obtaining an oyster of size $\mathrm { n } ^ { \circ } 3$ is 0.695. d. The health service selected an oyster of size $\mathrm { n } ^ { \circ } 3$. What is the probability that it is a flat oyster?
  2. The mass of an oyster can be modeled by a random variable $X$ following the normal distribution with mean $\mu = 90$ and standard deviation $\sigma = 2$. a. Give the probability that the oyster selected from the oyster farmer's production has a mass between 87 g and 89 g. b. Give $\mathrm { P } ( \mathrm { X } \geqslant 91 )$.

Part B
This oyster farmer claims that $60 \%$ of his oysters have a mass greater than 91 g.
A restaurant owner would like to buy a large quantity of oysters but would first like to verify the oyster farmer's claim.
The restaurant owner purchases 10 dozen oysters from this oyster farmer, which we will consider as a sample of 120 oysters drawn at random. His production is large enough that we can treat it as sampling with replacement. He observes that 65 of these oysters have a mass greater than 91 g.
  1. Let F be the random variable that associates to any sample of 120 oysters the frequency of those with a mass greater than 91 g. After verifying the conditions of application, give an asymptotic confidence interval at the $95 \%$ level for the random variable F.
  2. What can the restaurant owner think of the oyster farmer's claim?
A factory produces mineral water in bottles. When the calcium level in a bottle is less than $6.5 \mathrm { mg }$ per litre, the water in that bottle is said to be very low in calcium.
The mineral water comes from two sources, noted ``source A'' and ``source B''. The probability that water from a bottle randomly selected from the daily production of source A is very low in calcium is 0.17. The probability that water from a bottle randomly selected from the daily production of source B is very low in calcium is 0.10. Source A supplies $70\%$ of the total daily production of water bottles and source B supplies the rest of this production. A water bottle is randomly selected from the total daily production. We consider the following events: A: ``The water bottle comes from source A'' B: ``The water bottle comes from source B'' $S$: ``The water contained in the water bottle is very low in calcium''.
  1. Determine the probability of event $A \cap S$.
  2. Show that the probability of event $S$ equals 0.149.
  3. Calculate the probability that the water contained in a bottle comes from source A given that it is very low in calcium.
  4. The day after heavy rain, the factory takes a sample of 1000 bottles from source A. Among these bottles, 211 contain water that is very low in calcium. Give an interval to estimate at the $95\%$ confidence level the proportion of bottles containing water that is very low in calcium in the entire production of source A after this weather event.
Consider the probability tree opposite: [Figure]
What is the probability of event $B$ ? a. 0.12 b. 0.2 c. 0.24 d. 0.5
A company manufactures spherical wooden balls using two production machines A and B. The company considers that a ball can be sold only when its diameter is between $0.9 \mathrm{~cm}$ and $1.1 \mathrm{~cm}$.
Parts A, B and C are independent.
Part A
A study of the operation of the machines made it possible to establish the following results:
  • $96\%$ of daily production is saleable.
  • Machine A provides $60\%$ of daily production.
  • The proportion of saleable balls among the production of machine A is $98\%$.

A ball is chosen at random from the production of a given day. The following events are defined: $A$: ``the ball was manufactured by machine A''; $B$: ``the ball was manufactured by machine B''; $V$: ``the ball is saleable''.
  1. Determine the probability that the chosen ball is saleable and comes from machine A.
  2. Justify that $P(B \cap V) = 0.372$ and deduce the probability that the chosen ball is saleable given that it comes from machine B.
  3. A technician claims that $70\%$ of non-saleable balls come from machine B. Is he correct?

Part B
  1. A statistical study leads to modelling the diameter of a ball randomly selected from the production of machine B by a random variable $X$ which follows a normal distribution with mean $\mu = 1$ and standard deviation $\sigma = 0.055$. Verify that the probability that a ball produced by machine B is saleable is indeed that found in Part A, to the nearest hundredth.
  2. In the same way, the diameter of a ball randomly selected from the production of machine A is modelled using a random variable $Y$ which follows a normal distribution with mean $\mu = 1$ and standard deviation $\sigma'$, $\sigma'$ being a strictly positive real number. Given that $P(0.9 \leqslant Y \leqslant 1.1) = 0.98$, determine an approximate value to the nearest thousandth of $\sigma'$.

Part C
The saleable balls then pass through a machine that colours them randomly and with equal probability in white, black, blue, yellow or red. After being mixed, the balls are packaged in bags. The quantity produced is large enough that filling a bag can be treated as successive sampling with replacement of balls from daily production.
  1. In this question only, the bags are all composed of 40 balls. a. A bag of balls is chosen at random. Determine the probability that the chosen bag contains exactly 10 black balls. Round the result to $10^{-3}$. b. In a bag of 40 balls, 12 black balls were counted. Does this observation allow us to question the adjustment of the machine that colours the balls?
  2. If the company wishes the probability of obtaining at least one black ball in a bag to be greater than or equal to $99\%$, what is the minimum number of balls each bag must contain to achieve this objective?
A light bulb manufacturer has two machines, denoted A and B. Machine A provides $65\%$ of production, and machine B provides the rest. Some light bulbs have a manufacturing defect:
  • at the output of machine $\mathrm{A}$, $8\%$ of light bulbs have a defect;
  • at the output of machine B, $5\%$ of light bulbs have a defect.
The following events are defined:
  • A: ``the light bulb comes from machine A'';
  • B: ``the light bulb comes from machine B'';
  • $D$: ``the light bulb has a defect''.

  1. A light bulb is randomly selected from the total production of one day. a. Construct a probability tree representing the situation. b. Show that the probability of drawing a light bulb without a defect is equal to 0.9305. c. The light bulb drawn has no defect. Calculate the probability that it comes from machine A.
  2. 10 light bulbs are randomly selected from the production of one day at the output of machine A. The size of the stock allows us to consider the trials as independent and to assimilate the draws to draws with replacement. Calculate the probability of obtaining at least 9 light bulbs without a defect.
A market gardener specializes in strawberry production.
Part A: strawberry production
The market gardener produces strawberries in two greenhouses denoted A and B; $55\%$ of strawberry flowers are in greenhouse A, and $45\%$ in greenhouse B. In greenhouse A, the probability that each flower produces fruit is equal to 0.88; in greenhouse B, it is equal to 0.84.
For each of the following propositions, indicate whether it is true or false by justifying the answer. An unjustified answer will not be taken into account.
Proposition 1: The probability that a strawberry flower, chosen at random from this farm, produces fruit is equal to 0.862.
Proposition 2: It is observed that a flower, chosen at random from this farm, produces fruit. The probability that it is located in greenhouse A, rounded to the nearest thousandth, is equal to 0.439.
Part B: strawberry packaging
Strawberries are packaged in trays. The mass (expressed in grams) of a tray can be modeled by a random variable $X$ which follows the normal distribution with mean $\mu = 250$ and standard deviation $\sigma$.
  1. We are given $P ( X \leqslant 237 ) = 0.14$. Calculate the probability of the event ``the mass of the tray is between 237 and 263 grams''.
  2. Let $Y$ be the random variable defined by: $Y = \frac { X - 250 } { \sigma }$. a. What is the distribution of the random variable $Y$? b. Prove that $P \left( Y \leqslant - \frac { 13 } { \sigma } \right) = 0.14$. c. Deduce the value of $\sigma$ rounded to the nearest integer.
  3. In this question, we assume that $\sigma$ equals 12. We denote by $n$ and $m$ two integers. a. A tray is compliant if its mass, expressed in grams, lies in the interval $[ 250 - n ; 250 + n ]$. Determine the smallest value of $n$ for a tray to be compliant with a probability greater than or equal to $95\%$. b. In this question, we consider that a tray is compliant if its mass, expressed in grams, lies in the interval $[230; m ]$. Determine the smallest value of $m$ for a tray to be compliant with a probability greater than or equal to $95\%$.
Exercise 1 Common to all candidates
6 POINTS
The three parts are independent. Probability results should be rounded to $10^{-3}$ near.
Part 1
It is estimated that in 2013 the world population consists of 4.6 billion people aged 20 to 79 years and that $46.1\%$ of people aged 20 to 79 years live in rural areas and $53.9\%$ in urban areas. In 2013, according to the International Diabetes Federation, $9.9\%$ of the world population aged 20 to 79 years living in urban areas suffers from diabetes and $6.4\%$ of the world population aged 20 to 79 years living in rural areas suffers from diabetes.
A person aged 20 to 79 years is randomly selected. We denote: $R$ the event: ``the chosen person lives in a rural area'', $D$ the event: ``the chosen person suffers from diabetes''.
  1. Translate this situation using a probability tree.
  2. a. Calculate the probability that the interviewed person is diabetic. b. The chosen person is diabetic. What is the probability that they live in a rural area?

Part 2
A person is said to be hypoglycemic if their fasting blood glucose is less than $60 \mathrm{mg}.\mathrm{dL}^{-1}$ and they are hyperglycemic if their fasting blood glucose is greater than $110 \mathrm{mg}.\mathrm{dL}^{-1}$. Fasting blood glucose is considered ``normal'' if it is between $70 \mathrm{mg}.\mathrm{dL}^{-1}$ and $110 \mathrm{mg}.\mathrm{dL}^{-1}$. People with a blood glucose level between 60 and $70 \mathrm{mg}.\mathrm{rdL}^{-1}$ are not subject to special monitoring. An adult is randomly chosen from this population. A study established that the probability that they are hyperglycemic is 0.052 to $10^{-3}$ near. In the following, we will assume that this probability is equal to 0.052. We model the fasting blood glucose, expressed in $\mathrm{mg}.\mathrm{dL}^{-1}$, of an adult from a given population, by a random variable $X$ which follows a normal distribution with mean $\mu$ and standard deviation $\sigma$.
  1. What is the probability that the chosen person has ``normal'' fasting blood glucose?
  2. Determine the value of $\sigma$ rounded to the nearest tenth.
  3. In this question, we take $\sigma = 12$. Calculate the probability that the chosen person is hypoglycemic.

Part 3
In order to estimate the proportion, for the year 2013, of people diagnosed with diabetes in the French population aged 20 to 79 years, 10000 people are randomly interviewed. In the sample studied, 716 people were diagnosed with diabetes.
  1. Using a confidence interval at the $95\%$ confidence level, estimate the proportion of people diagnosed with diabetes in the French population aged 20 to 79 years.
  2. What should be the minimum number of people to interview if we want to obtain a confidence interval with amplitude less than or equal to 0.01?
We denote by $p$ the unknown proportion of young people aged 16 to 24 years who practice illegal downloading on the internet at least once a week.
A young person participating in protocol $( \mathscr { P } )$ is randomly selected. The protocol $( \mathscr { P } )$ is as follows: each young person rolls a fair 6-sided die; if the result is even, the young person answers sincerely; if the result is ``1'', the young person must answer ``Yes''; if the result is ``3 or 5'', the young person must answer ``No''.
We denote: $R$ the event ``the result of the roll is even'', $O$ the event ``the young person answered Yes''.
1. Probability calculations
Reproduce and complete the weighted tree diagram.
Deduce that the probability $q$ of the event ``the young person answered Yes'' is: $$q = \frac { 1 } { 2 } p + \frac { 1 } { 6 }$$
2. Confidence interval
a. At the request of Hadopi, a polling institute conducts a survey according to protocol $( \mathscr { P } )$. On a sample of size 1500, it counts 625 ``Yes'' responses. Give a confidence interval, at the 95\% confidence level, for the proportion $q$ of young people who answer ``Yes'' to such a survey, among the population of young French people aged 16 to 24 years. b. What can be concluded about the proportion $p$ of young people who practice illegal downloading on the internet at least once a week?
Exercise 3 (Candidates who have NOT followed the specialization course)
5 POINTS
We have a fair die with 6 faces numbered 1 to 6 and 2 coins A and B each having one heads side and one tails side. A game consists of rolling the die one or more times. After each die roll, if we get 1 or 2, then we flip coin A, if we get 3 or 4, then we flip coin B and if we get 5 or 6, then we flip neither of the two coins. At the beginning of the game, both coins are on the tails side.
  1. In the algorithm below, 0 codes the tails side of a coin and 1 codes the heads side. If $a$ codes the side of coin A at a given moment, then $1 - a$ codes the side of coin A after flipping it.

\begin{verbatim} Variables: a, b, d, s are integers i, n are integers greater than or equal to 1 Initialization: a takes the value 0 b takes the value 0 Input n Processing: For i going from 1 to n do d takes the value of a random integer between 1 and 6 If d <= 2 then a takes the value 1 - a else If d <= 4 | then b takes the value 1 - b EndIf EndIf s takes the value a + b EndFor Output: Display s \end{verbatim}
a. We execute this algorithm by inputting $n = 3$ and assuming that the random values generated successively for $d$ are $1; 6$ and 4. Copy and complete the table given below containing the state of the variables during the execution of the algorithm:
variables$i$$d$$a$$b$$s$
initialization
$1^{\text{st}}$ loop iteration
$2^{\text{nd}}$ loop iteration
$3^{\text{rd}}$ loop iteration

b. Does this algorithm allow us to decide whether at the end both coins are on the heads side?
2. For every natural integer $n$, we denote:
  • $X_{n}$ the event: ``After $n$ die rolls, both coins are on the tails side''
  • $Y_{n}$ the event: ``After $n$ die rolls, one coin is on the heads side and the other is on the tails side''
  • $Z_{n}$ the event: ``After $n$ die rolls, both coins are on the heads side''.

Moreover, we denote $x_{n} = P(X_{n}); y_{n} = P(Y_{n})$ and $z_{n} = P(Z_{n})$ the respective probabilities of events $X_{n}, Y_{n}$ and $Z_{n}$. a. Give the probabilities $x_{0}, y_{0}$ and $z_{0}$ respectively that at the beginning of the game there are 0, 1 or 2 coins on the heads side. b. Justify that $P_{X_{n}}(X_{n+1}) = \frac{1}{3}$. c. Copy the tree below and complete the probabilities on its branches, some of which may be zero. d. For every natural integer $n$, express $z_{n}$ as a function of $x_{n}$ and $y_{n}$. e. Deduce that, for every natural integer $n$, $y_{n+1} = -\frac{1}{3} y_{n} + \frac{2}{3}$. f. We set, for every natural integer $n$, $b_{n} = y_{n} - \frac{1}{2}$.
Show that the sequence $(b_{n})$ is geometric. Deduce that, for every natural integer $n$, $y_{n} = \frac{1}{2} - \frac{1}{2} \times \left(-\frac{1}{3}\right)^{n}$. g. Calculate $\lim_{n \rightarrow +\infty} y_{n}$.
Interpret the result.
For each of the four statements below, indicate whether it is true or false, by justifying the answer. One point is awarded for each correct answer with proper justification. An answer without justification is not taken into account. An absence of answer is not penalized.
  1. We have two dice, identical in appearance, one of which is biased so that 6 appears with probability $\frac{1}{2}$. We take one of the two dice at random, roll it, and obtain 6. Statement 1: the probability that the die rolled is the biased die is equal to $\frac{2}{3}$.
  2. In the complex plane, consider the points M and N with affixes respectively $z_{\mathrm{M}} = 2 \mathrm{e}^{-\mathrm{i} \frac{\pi}{3}}$ and $z_{\mathrm{N}} = \frac{3 - \mathrm{i}}{2 + \mathrm{i}}$. Statement 2: the line $(MN)$ is parallel to the imaginary axis.
  3. In an orthonormal frame $(\mathrm{O}, \vec{\imath}, \vec{\jmath}, \vec{k})$ of space, consider the line $d$ with parametric representation: $\left\{ \begin{array}{l} x = 1 + t \\ y = 2 \\ z = 3 + 2t \end{array} \quad t \in \mathbf{R} \right.$. Consider the points $\mathrm{A}$, $\mathrm{B}$ and $\mathrm{C}$ with $\mathrm{A}(-2; 2; 3)$, $\mathrm{B}(0; 1; 2)$ and $\mathrm{C}(4; 2; 0)$. We admit that the points $\mathrm{A}$, $\mathrm{B}$ and $\mathrm{C}$ are not collinear. Statement 3: the line $d$ is orthogonal to the plane (ABC).
  4. In an orthonormal frame $(\mathrm{O}, \vec{\imath}, \vec{\jmath}, \vec{k})$ of space, consider the line $d$ with parametric representation: $\left\{ \begin{array}{l} x = 1 + t \\ y = 2 \\ z = 3 + 2t \end{array} \quad t \in \mathbf{R} \right.$. Consider the line $\Delta$ passing through the point $\mathrm{D}(1; 4; 1)$ and with direction vector $\vec{v}(2; 1; 3)$. Statement 4: the line $d$ and the line $\Delta$ are not coplanar.
Exercise 1
4 points
Common to all candidates
Parts $\mathrm { A } , \mathrm { B }$ and C can be treated independently. Throughout the exercise, results should be rounded, if necessary, to the nearest thousandth.
Part A
A merchant receives the results of a market study on consumer habits in France. According to this study:
  • $54 \%$ of consumers prefer products of French manufacture;
  • $65 \%$ of consumers regularly buy products from organic agriculture, and among them $72 \%$ prefer products of French manufacture.

A consumer is chosen at random. The following events are considered:
  • B: ``a consumer regularly buys products from organic agriculture'';
  • $F$ : ``a consumer prefers products of French manufacture''.

We denote $P ( A )$ the probability of event $A$ and $P _ { C } ( A )$ the probability of $A$ given $C$.
  1. Justify that $P ( \bar { B } \cap F ) = 0.072$.
  2. Calculate $P _ { F } ( \bar { B } )$.
  3. A consumer is chosen who does not regularly buy products from organic agriculture. What is the probability that he prefers products of French manufacture?

Part B
The merchant is interested in the quantity in kilograms of organic flour sold each month at retail in his store. This quantity is modeled by a random variable $X$ which follows the normal distribution with mean $\mu = 90$ and standard deviation $\sigma = 2$.
  1. At the beginning of each month, the merchant ensures he has 95 kg in stock.

What is the probability that he cannot meet customer demand during the month?
2. Determine an approximate value to the nearest hundredth of the real number $a$ such that $P ( X < a ) = 0.02$.
Interpret the result in the context of the exercise.
Part C
In this market study, it is specified that $46.8 \%$ of consumers in France prefer local products. The merchant observes that among his 2500 customers, 1025 regularly buy local products. Is his customer base representative of consumers in France?
The operator of a communal forest decides to fell trees in order to sell them, either to residents or to businesses. It is assumed that:
  • among the felled trees, $30 \%$ are oaks, $50 \%$ are firs and the others are trees of secondary species (which means they are of lesser value);
  • $45.9 \%$ of the oaks and $80 \%$ of the firs felled are sold to residents of the commune;
  • three quarters of the felled trees of secondary species are sold to businesses.

Among the felled trees, one is chosen at random. The following events are considered:
  • C: ``the felled tree is an oak'';
  • $S$: ``the felled tree is a fir'';
  • $E$: ``the felled tree is a tree of secondary species'';
  • $H$: ``the felled tree is sold to a resident of the commune''.

  1. Construct a complete weighted tree representing the situation.
  2. Calculate the probability that the felled tree is an oak sold to a resident of the commune.
  3. Justify that the probability that the felled tree is sold to a resident of the commune is equal to 0.5877.
  4. What is the probability that a felled tree sold to a resident of the commune is a fir? The result will be given rounded to $10^{-3}$.
Exercise 2 (4 points)
The flu virus affects each year, during the winter period, part of the population of a city. Vaccination against the flu is possible; it must be renewed each year.
Part A
A study conducted in the city's population at the end of the winter period found that:
  • $40 \%$ of the population is vaccinated;
  • $8 \%$ of vaccinated people contracted the flu;
  • $20 \%$ of the population contracted the flu.

A person is chosen at random from the city's population and we consider the events: $V$: ``the person is vaccinated against the flu''; $G$: ``the person contracted the flu''.
  1. a. Give the probability of event $G$. b. Reproduce the probability tree below and complete the blanks indicated on four of its branches.
  2. Determine the probability that the chosen person contracted the flu and is vaccinated.
  3. The chosen person is not vaccinated. Show that the probability that they contracted the flu is equal to 0.28.

Part B
In this part, the probabilities requested will be given to $10 ^ { - 3 }$ near.
A pharmaceutical laboratory conducts a study on vaccination against the flu in this city. After the winter period, $n$ inhabitants of the city are randomly interviewed, assuming that this choice amounts to $n$ successive independent draws with replacement. We assume that the probability that a person chosen at random in the city is vaccinated against the flu is equal to 0.4. Let $X$ be the random variable equal to the number of vaccinated people among the $n$ interviewed.
  1. What is the probability distribution followed by the random variable $X$?
  2. In this question, we assume that $n = 40$. a. Determine the probability that exactly 15 of the 40 people interviewed are vaccinated. b. Determine the probability that at least half of the people interviewed are vaccinated.
  3. A sample of 3750 inhabitants of the city is interviewed, that is, we assume here that $n = 3750$. Let $Z$ be the random variable defined by: $Z = \frac { X - 1500 } { 30 }$. We admit that the probability distribution of the random variable $Z$ can be approximated by the standard normal distribution. Using this approximation, determine the probability that there are between 1450 and 1550 vaccinated individuals in the sample interviewed.
This club makes group orders of bearings for its members from two suppliers A and B.
  • Supplier A offers higher prices but the bearings it sells are defect-free with a probability of 0.97.
  • Supplier B offers more advantageous prices but its bearings are defective with a probability of 0.05.

A bearing is chosen at random from the club's stock and we consider the events: $A$: ``the bearing comes from supplier A'', $B$: ``the bearing comes from supplier B'', $D$: ``the bearing is defective''.
  1. The club buys $40\%$ of its bearings from supplier A and the rest from supplier B. a. Calculate the probability that the bearing comes from supplier A and is defective. b. The bearing is defective. Calculate the probability that it comes from supplier B.
  2. If the club wants less than $3.5\%$ of the bearings to be defective, what minimum proportion of bearings should it order from supplier A?
A company specializes in the sale of tiles.
Parts A, B and C are independent.
Part A
We assume in this part that the company sells batches of tiles containing $25\%$ of tiles with pattern and $75\%$ of white tiles. During a quality control, it is observed that:
  • $2.25\%$ of the tiles are cracked;
  • $6\%$ of the tiles with pattern are cracked.
A tile is randomly selected. We denote by $M$ the event ``the tile has a pattern'' and $F$ the event ``the tile is cracked''.
  1. Translate the situation using a probability tree.
  2. We know that the selected tile is cracked. Prove that the probability that it is a tile with pattern is $\frac{2}{3}$.
  3. Calculate $P_{\bar{M}}(F)$, the probability of $F$ given $\bar{M}$.

Part B
We model the thickness in millimeters of a randomly selected tile by a random variable $X$ that follows a normal distribution with mean $\mu = 11$ and standard deviation $\sigma$.
A tile is marketable if its thickness measures between $10.1\text{ mm}$ and $11.9\text{ mm}$. We know that $99\%$ of the tiles are marketable.
  1. Prove that $P(X < 10.1) = 0.005$.
  2. We introduce the random variable $Z$ such that $$Z = \frac{X - 11}{\sigma}.$$ a. Give the distribution followed by the random variable $Z$. b. Prove that $P\left(Z \leqslant -\frac{0.9}{\sigma}\right) = 0.005$. c. Deduce the value of $\sigma$ rounded to the nearest hundredth.

Part C
We consider the function $f$ defined on $[0; 2\pi]$ by $$f(x) = -1.5\cos(x) + 1.5$$ We admit that the function $f$ is continuous on $[0; 2\pi]$. We denote by $\mathscr{C}_1$ the representative curve of the function $f$ in an orthonormal coordinate system.
  1. Prove that the function $f$ is positive on $[0; 2\pi]$.
  2. In the figure above, the curve drawn in dashes, denoted $\mathscr{C}_2$, is the curve symmetric to $\mathscr{C}_1$ with respect to the $x$-axis. The shape of a tile is that of the region bounded by the curves $\mathscr{C}_1$ and $\mathscr{C}_2$. We denote by $\mathscr{A}$ its area, expressed in square units. Calculate $\mathscr{A}$.
In France, the consumption of organic products has been growing for several years.
In 2017, the country had $52\%$ women. That same year, $92\%$ of French people had already consumed organic products. Furthermore, among consumers of organic products, $55\%$ were women.
We randomly choose a person from the file of French people in 2017. We denote:
  • $F$ the event ``the chosen person is a woman'';
  • $H$ the event ``the chosen person is a man'';
  • $B$ the event ``the chosen person has already consumed organic products''.

  1. Translate the numerical data from the statement using events $F$ and $B$.
  2. a. Show that $P(F \cap B) = 0{,}506$. b. Deduce the probability that a person consumed organic products in 2017, given that they are a woman.
  3. Calculate $P_H(\bar{B})$. Interpret this result in the context of the exercise.
We have two urns $U$ and $V$ containing balls. On each of the balls is written one of the numbers $-1$, $1$, or $2$.
Urn $U$ contains one ball bearing the number 1 and three balls bearing the number $-1$. Urn $V$ contains one ball bearing the number 1 and three balls bearing the number 2. We consider a game in which each round proceeds as follows: first we draw at random a ball from urn $U$, we note $x$ the number written on this ball and then we put it in urn $V$. In a second step, we draw at random a ball from urn $V$ and we note $y$ the number written on this ball. We consider the following events:
  • $U _ { 1 }$: ``we draw a ball bearing the number 1 from urn $U$, that is $x = 1$'';
  • $U _ { - 1 }$: ``we draw a ball bearing the number $-1$ from urn $U$, that is $x = -1$'';
  • $V _ { 2 }$: ``we draw a ball bearing the number 2 from urn $V$, that is $y = 2$'';
  • $V _ { 1 }$: ``we draw a ball bearing the number 1 from urn $V$, that is $y = 1$'';
  • $V _ { - 1 }$: ``we draw a ball bearing the number $-1$ from urn $V$'', that is $y = -1$''.

  1. Copy and complete the probability tree.
  2. In this game, with each round we associate the complex number $z = x + \mathrm { i } y$.
    Calculate the probabilities of the following events. The answers will be justified. a. $A$: ``$z = -1 - \mathrm { i }$''; b. $B$: ``$z$ is a solution of the equation $t ^ { 2 } + 2 t + 5 = 0$''; c. $C$: ``In the complex plane with an orthonormal coordinate system $( \mathrm { O } ; \vec { u } , \vec { v } )$ the point $M$ with affixe $z$ belongs to the disk with center O and radius 2''.
  3. During a round, we obtain the number 1 on each of the balls drawn. Show that the complex number $z$ associated with this round satisfies $z ^ { 2020 } = - 2 ^ { 1010 }$.
Let $n$ be a natural number greater than or equal to 2.
A bag contains $n$ indistinguishable balls to the touch. All these balls have one ``HEADS'' side and one ``TAILS'' side except one which has two ``TAILS'' sides.
A ball is chosen at random from the bag and then tossed. The probability of obtaining the ``TAILS'' side is equal to: Answer A: $\frac { n - 1 } { n } \quad$ Answer B: $\frac { n + 1 } { 2 n } \quad$ Answer C: $\frac { 1 } { 2 } \quad$ Answer D: $\frac { n - 1 } { 2 n }$
This exercise is a multiple choice questionnaire. For each of the following questions, only one of the four proposed answers is correct.
A correct answer earns one point. An incorrect answer, a multiple answer, or the absence of an answer to a question earns or deducts no points.
PART I
In a mail processing centre, a machine is equipped with an automatic optical reader for recognizing postal addresses. This reading system correctly recognizes $97\%$ of addresses; the remaining mail, which will be described as unreadable for the machine, is directed to a centre employee responsible for reading the addresses. This machine has just read nine addresses. We denote by $X$ the random variable that gives the number of unreadable addresses among these nine addresses. We assume that $X$ follows the binomial distribution with parameters $n = 9$ and $p = 0.03$.
  1. The probability that none of the nine addresses is unreadable is equal, to the nearest hundredth, to: a. 0 b. 1 c. 0.24 d. 0.76
  2. The probability that exactly two of the nine addresses are unreadable for the machine is: a. $\binom{9}{2} \times 0.97^{2} \times 0.03^{7}$ b. $\binom{7}{2} \times 0.97^{2} \times 0.03^{7}$ c. $\binom{9}{2} \times 0.97^{7} \times 0.03^{2}$ d. $\binom{7}{2} \times 0.97^{7} \times 0.03^{2}$
  3. The probability that at least one of the nine addresses is unreadable for the machine is: a. $P(X < 1)$ b. $P(X \leqslant 1)$ c. $P(X \geqslant 2)$ d. $1 - P(X = 0)$

PART II
An urn contains 5 green balls and 3 white balls, indistinguishable to the touch. We draw at random successively and without replacement two balls from the urn. We consider the following events:
  • $V_{1}$: "the first ball drawn is green";
  • $B_{1}$: "the first ball drawn is white";
  • $V_{2}$: "the second ball drawn is green";
  • $B_{2}$: "the second ball drawn is white".

  1. The probability of $V_{2}$ given that $V_{1}$ is realized, denoted $P_{V_{1}}\left(V_{2}\right)$, is equal to: a. $\frac{5}{8}$ b. $\frac{4}{7}$ c. $\frac{5}{14}$ d. $\frac{20}{56}$
  2. The probability of event $V_{2}$ is equal to: a. $\frac{5}{8}$ b. $\frac{5}{7}$ c. $\frac{3}{28}$ d. $\frac{9}{7}$
A company manufactures microchips. Each chip can have two defects denoted A and B.
A statistical study shows that $2.8\%$ of chips have defect A, $2.2\%$ of chips have defect B, and fortunately, $95.4\%$ of chips have neither of the two defects.
The probability that a randomly selected chip has both defects is: a. 0.05 b. 0.004 c. 0.046 d. We cannot know
A hotel located near a prehistoric tourism site offers two visits in the surrounding area, one to a museum and one to a cave.
A study showed that $70\%$ of the hotel's clients visit the museum. Furthermore, among clients visiting the museum, $60\%$ visit the cave. The study also shows that $6\%$ of the hotel's clients make no visits. We randomly question a hotel client and note:
  • $M$ the event: ``the client visits the museum'';
  • $G$ the event: ``the client visits the cave''.
We denote by $\bar { M }$ the complementary event of $M$, $\bar { G }$ the complementary event of $G$, and for any event $E$, we denote by $p ( E )$ the probability of $E$. Thus, according to the problem statement, we have: $p ( \bar { M } \cap \bar { G } ) = 0.06$.
  1. a. Verify that $p _ { \bar { M } } ( \bar { G } ) = 0.2$, where $p _ { \bar { M } } ( \bar { G } )$ denotes the probability that the questioned client does not visit the cave given that he does not visit the museum. b. The weighted tree opposite models the situation. Copy and complete this tree by indicating on each branch the associated probability. c. What is the probability of the event ``the client visits the cave and does not visit the museum''? d. Show that $p ( G ) = 0.66$.
  2. The hotel manager claims that among clients who visit the cave, more than half also visit the museum. Is this claim correct?
  3. The prices for visits are as follows:
    • museum visit: 12 euros;
    • cave visit: 5 euros.
    We consider the random variable $T$ which models the amount spent by a hotel client for these visits. a. Give the probability distribution of $T$. Present the results in the form of a table. b. Calculate the mathematical expectation of $T$. c. For profitability reasons, the hotel manager estimates that the average amount of visit revenues must be greater than 700 euros per day. Determine the average number of clients per day needed to achieve this objective.
  4. To increase revenues, the manager wishes the expectation of the random variable modeling the amount spent by a hotel client for these visits to increase to 15 euros, without changing the museum visit price which remains at 12 euros. What price should be set for the cave visit to achieve this objective? (We will assume that the increase in the cave entrance price does not change the frequency of visits to the two sites).
  5. We randomly choose 100 hotel clients, treating this choice as a draw with replacement. What is the probability that at least three-quarters of these clients visited the cave during their stay at the hotel? Give a value of the result to $10 ^ { - 3 }$ near.