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Statistics. 5.2. Quiz 6. A quick quiz consists of a true/false question followed by a multiple-choice question with four possible answers ( a,b,c,d ). An Unprepared student makes random guesses for both answers. a. What is the probability of that both answers are correct

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Statistics

Statistics

5.2


Quiz 6

Quiz 6

A quick quiz consists of a true/false question followed by a multiple-choice question with four possible answers (a,b,c,d). An Unprepared student makes random guesses for both answers.

a. What is the probability of that both answers are correct

b. Is guessing a good strategy?


Random variables

Random Variables

Everyone look at figure 5-1 on page 204 of our book.

  • A random variable is a variable (typically represented by x) that has a single numerical value, determined by chance, for each outcome of a procedure


Random variables1

Random Variables

Everyone look at figure 5-1 on page 204 of our book.

  • A random variable is a variable (typically represented by x) that has a single numerical value, determined by chance, for each outcome of a procedure

  • A probability distribution is a description that gives the probability for each value of the random variable. It is often expressed in the format of a graph, table, or formula.


Random variables2

Random Variables

Everyone look at figure 5-1 on page 204 of our book.

  • A random variable is a variable (typically represented by x) that has a single numerical value, determined by chance, for each outcome of a procedure

  • A probability distribution is a description that gives the probability for each value of the random variable. It is often expressed in the format of a graph, table, or formula.


Random variables3

Random Variables

  • A discrete random variable has either a finite number of values or a countable number of values.


Random variables4

Random Variables

  • A discrete random variable has either a finite number of values or a countable number of values.

  • A continuous random variable has infinitely many values, and those value can be associated with measurements on a continuous scale without gaps or interruptions.


Random variables5

Random Variables

  • A discrete random variable has either a finite number of values or a countable number of values.

  • A continuous random variable has infinitely many values, and those value can be associated with measurements on a continuous scale without gaps or interruptions.


Random variables6

Random Variables

Determine whether the given random variable is discrete or continuous.

a. The total amount in (ounces) of soft drinks that you consumed in the past year.

b. The number of cans of soft drinks that you consumed in the past year.

c. The number of movies currently playing in U.S. theaters.

d. The running time of a randomly selected movie.

e. The cost of making a randomly selected movie.


Random variables7

Random Variables

We use probability histograms to graph a probability distribution


Random variables8

Random Variables

We use probability histograms to graph a probability distribution


Random variables9

Random Variables

Requirements for a Probability Distribution

1. where x assumes all possible values.

2. for every individual value of x


Random variables10

Random Variables

Requirements for a Probability Distribution

1. where x assumes all possible values.

2. for every individual value of x.


Random variables11

Random Variables

Based on a survey conducted by Frank N. Magid Associates, Table 5-2 lists the probabilities for the number of cell phones in use per household. Does the table below describe a probability Distribution?


Random variables12

Random Variables

Does (where can be 0, 1, 2, 3, or 4) determine a probability distribution?


Random variables13

Random Variables

Does (where can be 0, 1, 2, 3, or 4) determine a probability distribution?


Random variables14

Random Variables

Does (where can be 0, 1, 2, 3, or 4) determine a probability distribution?


Random variables15

Random Variables

Mean, Variance, and Standard Deviation

  • Mean for a probability distribution


Random variables16

Random Variables

Mean, Variance, and Standard Deviation

  • Mean for a probability distribution

  • Variance for a probability distribution


Random variables17

Random Variables

Mean, Variance, and Standard Deviation

  • Mean for a probability distribution

  • Variance for a probability distribution

  • Variance for a probability distribution


Random variables18

Random Variables

Mean, Variance, and Standard Deviation

  • Mean for a probability distribution

  • Variance for a probability distribution

  • Variance for a probability distribution

  • Standard Deviation for a probability distribution


Random variables19

Random Variables

Mean, Variance, and Standard Deviation

  • Mean for a probability distribution

  • Variance for a probability distribution

  • Variance for a probability distribution

  • Standard Deviation for a probability distribution

    Lets do example 5 in excel!, and then do problem 3 on the worksheet


Random variables20

Random Variables

Determine whether the following is a probability distribution and if so find its mean and standard deviation . Groups of five babies are randomly selected. In each group, the random variable x is the number of babies with green eyes (0+ denotes a positive probability value that is very small)


Random variables21

Random Variables

Determine whether the following is a probability distribution and if so find its mean and standard deviation . Groups of five babies are randomly selected. In each group, the random variable x is the number of babies with green eyes (0+ denotes a positive probability value that is very small)


Random variables22

Random Variables

Determine whether the following is a probability distribution and if so find its mean and standard deviation . Groups of five babies are randomly selected. In each group, the random variable x is the number of babies with green eyes (0+ denotes a positive probability value that is very small)


Random variables23

Random Variables

Determine whether the following is a probability distribution and if so find its mean and standard deviation . Groups of five babies are randomly selected. In each group, the random variable x is the number of babies with green eyes (0+ denotes a positive probability value that is very small)


Random variables24

Random Variables

Round off rule for

Round results by carrying one more decimal place than the number of decimal places used for the random variable x. If the values of x are integers, round to one decimal place.


Random variables25

Random Variables

Round off rule for

Round results by carrying one more decimal place than the number of decimal places used for the random variable x. If the values of x are integers, round to one decimal place.

Recall the range rule of thumb


Random variables26

Random Variables

Round off rule for

Round results by carrying one more decimal place than the number of decimal places used for the random variable x. If the values of x are integers, round to one decimal place.

Recall the range rule of thumb


Random variables27

Random Variables

Round off rule for

Round results by carrying one more decimal place than the number of decimal places used for the random variable x. If the values of x are integers, round to one decimal place.

Recall the range rule of thumb


Random variables28

Random Variables

Round off rule for

Round results by carrying one more decimal place than the number of decimal places used for the random variable x. If the values of x are integers, round to one decimal place.

Recall the range rule of thumb


Random variables29

Random Variables

Use the range rule of thumb to identify a range of values containing the usual number of peas with green pods. Based on this is it unusual to get only one pea with a green pod? Explain.


Random variables30

Random Variables

Rare Event Rule for Inferential Statistics

If, under a given assumption(such that a coin is fair), the probability of a particular observed event (such as 992 heads in 1000 tosses of a coin) is extremely small, we conclude that the assumption is not correct.


Random variables31

Random Variables

Rare Event Rule for Inferential Statistics

If, under a given assumption(such that a coin is fair), the probability of a particular observed event (such as 992 heads in 1000 tosses of a coin) is extremely small, we conclude that the assumption is not correct.

  • Unusually high number of successes: x successes among n trials is an unusually high number of successes if the probability of x or more successes is unlikely with a probability of 0.05 or less.


Random variables32

Random Variables

Rare Event Rule for Inferential Statistics

If, under a given assumption(such that a coin is fair), the probability of a particular observed event (such as 992 heads in 1000 tosses of a coin) is extremely small, we conclude that the assumption is not correct.

  • Unusually high number of successes: x successes among n trials is an unusually high number of successes if the probability of x or more successes is unlikely with a probability of 0.05 or less.

  • Unusually low number of successes: x successes among n trials is an unusually low number of successes if the probability of x or fewer successes is unlikely with a probability of 0.05 or less.


Random variables33

Random Variables

Rare Event Rule for Inferential Statistics

If, under a given assumption(such that a coin is fair), the probability of a particular observed event (such as 992 heads in 1000 tosses of a coin) is extremely small, we conclude that the assumption is not correct.

  • Unusually high number of successes: x successes among n trials is an unusually high number of successes if the probability of x or more successes is unlikely with a probability of 0.05 or less.

  • Unusually low number of successes: x successes among n trials is an unusually low number of successes if the probability of x or fewer successes is unlikely with a probability of 0.05 or less.


Random variables34

Random Variables

a) Find the probability of getting exactly 3 peas with green pods .

b) Find the probability of getting 3 or fewer peas with green pods.

c) Which Probability is relevant to determine whether 3 is an unusually low number of peas with green pods: the result from part (a) or part (b).

d) Is 3 and unusually low number of peas with green pods? Why or why not?


Random variables35

Random Variables

a) Find the probability of getting exactly 3 peas with green pods . 0.023

b) Find the probability of getting 3 or fewer peas with green pods.

c) Which Probability is relevant to determine whether 3 is an unusually low number of peas with green pods: the result from part (a) or part (b).

d) Is 3 and unusually low number of peas with green pods? Why or why not?


Random variables36

Random Variables

a) Find the probability of getting exactly 3 peas with green pods . 0.023

b) Find the probability of getting 3 or fewer peas with green pods. 0.027

c) Which Probability is relevant to determine whether 3 is an unusually low number of peas with green pods: the result from part (a) or part (b).

d) Is 3 and unusually low number of peas with green pods? Why or why not?


Random variables37

Random Variables

a) Find the probability of getting exactly 3 peas with green pods . 0.023

b) Find the probability of getting 3 or fewer peas with green pods. 0.027

c) Which Probability is relevant to determine whether 3 is an unusually low number of peas with green pods: the result from part (a) or part (b). Part (b)

d) Is 3 and unusually low number of peas with green pods? Why or why not?


Random variables38

Random Variables

a) Find the probability of getting exactly 3 peas with green pods . 0.023

b) Find the probability of getting 3 or fewer peas with green pods. 0.027

c) Which Probability is relevant to determine whether 3 is an unusually low number of peas with green pods: the result from part (a) or part (b). Part (b)

d) Is 3 and unusually low number of peas with green pods? Why or why not? Yes since


Random variables39

Random Variables

Expected Value

The expected value of a discrete random variable is denoted by E, and it represents the mean value of its outcomes. It is obtained by finding the value of


Random variables40

Random Variables

Expected Value

The expected value of a discrete random variable is denoted by E, and it represents the mean value of its outcomes. It is obtained by finding the value of


Random variables41

Random Variables

You are considering placing a bet on the number 7 in roulette or red for roulette.


Random variables42

Random Variables

  • If you bet $5 on the number 7 in roulette, the probability of losing $5 is 37/38 and the probability making a net gain of $175 is 1/38. Let’s find the expected value if you bet on 7.


Random variables43

Random Variables

  • If you bet $5 on the number 7 in roulette, the probability of losing $5 is 37/38 and the probability making a net gain of $175 is 1/38. Let’s find the expected value if you bet on 7.


Random variables44

Random Variables

  • If you bet $5 on red, the probability of losing $5 is 20/38 and the probability making a net gain of $5 is 18/38. Let’s find the expected value if you bet on red.


Random variables45

Random Variables

  • If you bet $5 on red, the probability of losing $5 is 20/38 and the probability making a net gain of $5 is 18/38. Let’s find the expected value if you bet on red.


Homework

Homework!!!

  • 5-2: 1-17 odd ,21, 25, 27


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