Question 1

The weight of an object, measured to the nearest gram, is an example of a _____ random variable.

Accepted Answer

A)  continuous 
B)  discrete 
C)  nominal 
D)  mixed type 
A)  continuous 
B)  discrete 
C)  nominal 
D)  mixed type

Question 2

In a binomial experiment consisting of five trials, the number of different values that x (the number of successes) can assume is

Accepted Answer

A)  2. 
B)  5. 
C)  6. 
D)  10. 
A)  2. 
B)  5. 
C)  6. 
D)  10.

Question 3

The key difference between the binomial and hypergeometric distribution is that, with the hypergeometric distribution the

Accepted Answer

A)  probability of success must be less than 0.5. 
B)  probability of success changes from trial to trial. 
C)  trials are independent of each other. 
D)  random variable is continuous. 
A)  probability of success must be less than 0.5. 
B)  probability of success changes from trial to trial. 
C)  trials are independent of each other. 
D)  random variable is continuous.

Question 4

Random variable x has the probability function: f(x) =x/6 for x = 1,2 or 3. The expected value of x is

Accepted Answer

A)  0.333. 
B)  0.500. 
C)  2.000. 
D)  2.333. 
A)  0.333. 
B)  0.500. 
C)  2.000. 
D)  2.333.

The weight of an object, measured to the nearest gram, is an example of a _____ random variable.

In a binomial experiment consisting of five trials, the number of different values that x (the number of successes) can assume is

The key difference between the binomial and hypergeometric distribution is that, with the hypergeometric distribution the

Random variable x has the probability function: f(x) =x/6 for x = 1,2 or 3. The expected value of x is

Data and Statistics

Descriptive Statistics: Tabular and Graphical Displays

Descriptive Statistics: Numerical Measures

Introduction to Probability

Continuous Probability Distributions

Sampling and Sampling Distributions

Interval Estimation

Hypothesis Tests

Inference About Means and Proportions With Two Populations

Inferences About Population Variances

Comparing Multiple Proportions, Tests of Independence and Goodness of Fit

Experimental Design and Analysis of Variance

Simple Linear Regression

Multiple Regression

Regression Analysis: Model Building

Time Series Analysis and Forecasting

Nonparametric Methods

Decision Analysis

Index Numbers

Statistical Methods for Quality Control

Sample Survey

Filters

Exam 5: Discrete Probability Distributions

The weight of an object, measured to the nearest gram, is an example of a _____ random variable.

In a binomial experiment consisting of five trials, the number of different values that x (the number of successes) can assume is

The key difference between the binomial and hypergeometric distribution is that, with the hypergeometric distribution the

Random variable x has the probability function: f(x) =x/6 for x = 1,2 or 3. The expected value of x is

Data and Statistics

Descriptive Statistics: Tabular and Graphical Displays

Descriptive Statistics: Numerical Measures

Introduction to Probability

Continuous Probability Distributions

Sampling and Sampling Distributions

Interval Estimation

Hypothesis Tests

Inference About Means and Proportions With Two Populations

Inferences About Population Variances

Comparing Multiple Proportions, Tests of Independence and Goodness of Fit

Experimental Design and Analysis of Variance

Simple Linear Regression

Multiple Regression

Regression Analysis: Model Building

Time Series Analysis and Forecasting

Nonparametric Methods

Decision Analysis

Index Numbers

Statistical Methods for Quality Control

Sample Survey

Filters