Question 1

Performing a linear transformation can make any distribution normal.

Accepted Answer

A) True 
 B)False  False

Question 2

Based on the height data in the previous question: 
a. What percent of residents are between 65 inches and 71 inches tall? 
b. What percent of residents are taller than 72 inches? 
c. What percent of residents are shorter than 72 inches?

Accepted Answer

a. 68% 
b. 9% 
c. 91%

Question 3

Which of the following is NOT always true of a normal distribution?

Accepted Answer

A)  It is symmetric. 
B)  It has a mean of 0. 
C)  It is unimodal. 
D)  both a and b 
A)  It is symmetric. 
B)  It has a mean of 0. 
C)  It is unimodal. 
D)  both a and b B

Question 4

In a normal distribution, indicate what percent of scores fall: 
a. between the mean and 1 standard deviation above the mean 
b. between plus and minus 2 standard deviations of the mean. 
c. 3 standard deviations above or below the mean.

Accepted Answer

a. 68% 
b.

Question 5

The difference between "probable limits" and "confidence limits" is that the probable limits

Accepted Answer

A)  focus on estimating where a particular score is likely to lie using a known population mean. 
B)  estimate the kinds of means that we expect. 
C)  try to set limits that have a .95 probability of containing the population mean. 
D)  There is no difference. 
A)  focus on estimating where a particular score is likely to lie using a known population mean. 
B)  estimate the kinds of means that we expect. 
C)  try to set limits that have a .95 probability of containing the population mean. 
D)  There is no difference.

Question 6

If the salary of assistant professors in this university is normally distributed with a mean of $45,000 and a standard deviation of $1,500, what salary would have a z score of .97?

Accepted Answer

The answer of If the salary of assistant professors in...

Question 7

We care a great deal about areas under the normal distribution because

Accepted Answer

A)  they translate directly to expected proportions. 
B)  they are additive. 
C)  they allow us to calculate probabilities of categories of outcomes. 
D)  all of the above 
A)  they translate directly to expected proportions. 
B)  they are additive. 
C)  they allow us to calculate probabilities of categories of outcomes. 
D)  all of the above

Question 8

Assume that your class took an exam last week and the mean and standard deviation of the exam were 85 and 5, respectively. Your instructor told you that 30 percent of the students had a score of 90 or above. You would probably

Accepted Answer

A)  think that your instructor was out of her mind. 
B)  decide that your score of 80 would probably fall in the failing range. 
C)  conclude that the scores were not normally distributed. 
D)  conclude that such a set of scores could not possibly happen. 
A)  think that your instructor was out of her mind. 
B)  decide that your score of 80 would probably fall in the failing range. 
C)  conclude that the scores were not normally distributed. 
D)  conclude that such a set of scores could not possibly happen.

Question 9

The area under a particular portion of the normal curve is equivalent to theprobability of falling within that portion of the distribution.

Accepted Answer

A) True 
 B)False

Question 10

The probability that a student will score between plus or minus one standard deviation from the mean on an exam, assuming the scores are normally distributed, is approximately 68%.

Accepted Answer

A) True 
 B)False

Question 11

An example of a linear transformation is

Accepted Answer

A)  converting heights from feet to meters. 
B)  subtracting the value of the mean from each individual IQ score and dividing by the value of the standard deviation. 
C)  both a and b 
D)  none of the above 
A)  converting heights from feet to meters. 
B)  subtracting the value of the mean from each individual IQ score and dividing by the value of the standard deviation. 
C)  both a and b 
D)  none of the above

Question 12

Based on the previous data, we could conclude that 90% of the students are likely to fall between what heights?

Accepted Answer

90% of students will

Question 13

The normal distribution is

Accepted Answer

A)  most frequently observed for the distribution of small sample sizes. 
B)  characterized by a high degree of skewness. 
C)  a distribution with a known shape and other properties. 
D)  the distribution that we would expect for the salaries of basketball players. 
A)  most frequently observed for the distribution of small sample sizes. 
B)  characterized by a high degree of skewness. 
C)  a distribution with a known shape and other properties. 
D)  the distribution that we would expect for the salaries of basketball players.

Question 14

When we transform scores to a distribution that has a mean of 50 and a standard deviation of 10, those scores are called

Accepted Answer

A)  z scores. 
B)  t scores. 
C)  T scores. 
D)  stanine scores. 
A)  z scores. 
B)  t scores. 
C)  T scores. 
D)  stanine scores.

Question 15

The height of students in a dormitory is normally distributed with a mean of 68 inches and a standard deviation of 3 inches. Draw the distribution.

Accepted Answer

A sample d

Question 16

The basketball team lives in another dorm from those in the previous question. Their heights are normally distributed as well, with a mean height of 71 inches and a standard deviation of 2 inches. 
a. Draw their distribution on the same graph as students who lived in the first dorm (e.g., draw separate but overlapping distributions). 
b. What percent of students in the first dorm are at least as tall as the average basketball players? 
c. What percent of basketball players are taller than the average dorm resident?

Accepted Answer

a. A sampl

Question 17

The birth weight of healthy, full term infants in the United States is nearly normally distributed. The mean weight is 3,500 grams, and the standard deviation is 500 grams. 
  
a. What percent of healthy newborns will weigh more than 3,250 grams? 
b. What weights would 95% of all healthy newborns tend to fall between? 
c. What is the z score for an infant who weighs 2,750 grams? 
​

Accepted Answer

a. 69% 
b. 95% would

Question 18

The difference between the histogram of 175 behavior problem scores and a normal distribution is

Accepted Answer

A)  the normal distribution is continuous, while behavior problem scores are discrete. 
B)  the normal distribution is symmetric, while behavior problem scores may not be. 
C)  the ordinate of the normal distribution is density, the ordinate for behavior problems is frequency. 
D)  Each of the previous choices is correct. 
A)  the normal distribution is continuous, while behavior problem scores are discrete. 
B)  the normal distribution is symmetric, while behavior problem scores may not be. 
C)  the ordinate of the normal distribution is density, the ordinate for behavior problems is frequency. 
D)  Each of the previous choices is correct.

Question 19

If a population of behavior problem scores is reasonably approximated by a normal distribution, we would expect that the X axis would

Accepted Answer

A)  have values between 0 and 4. 
B)  have values between -1 and +1. 
C)  have only negative values. 
D)  We cannot say what the values on that axis would be. 
A)  have values between 0 and 4. 
B)  have values between -1 and +1. 
C)  have only negative values. 
D)  We cannot say what the values on that axis would be.

Question 20

The text discussed setting "probable limits" on an observation. These limits are those which have a

Accepted Answer

A)  50% chance of enclosing the value that the observation will have. 
B)  75% chance of enclosing the value that the observation will have. 
C)  80% chance of enclosing the value that the observation will have. 
D)  95% chance of enclosing the value that the observation will have. 
A)  50% chance of enclosing the value that the observation will have. 
B)  75% chance of enclosing the value that the observation will have. 
C)  80% chance of enclosing the value that the observation will have. 
D)  95% chance of enclosing the value that the observation will have.

Performing a linear transformation can make any distribution normal.

Based on the height data in the previous question: a. What percent of residents are between 65 inches and 71 inches tall? b. What percent of residents are taller than 72 inches? c. What percent of residents are shorter than 72 inches?

Which of the following is NOT always true of a normal distribution?

In a normal distribution, indicate what percent of scores fall: a. between the mean and 1 standard deviation above the mean b. between plus and minus 2 standard deviations of the mean. c. 3 standard deviations above or below the mean.

The difference between "probable limits" and "confidence limits" is that the probable limits

If the salary of assistant professors in this university is normally distributed with a mean of $45,000 and a standard deviation of $1,500, what salary would have a z score of .97?

We care a great deal about areas under the normal distribution because

Assume that your class took an exam last week and the mean and standard deviation of the exam were 85 and 5, respectively. Your instructor told you that 30 percent of the students had a score of 90 or above. You would probably

The area under a particular portion of the normal curve is equivalent to theprobability of falling within that portion of the distribution.

The probability that a student will score between plus or minus one standard deviation from the mean on an exam, assuming the scores are normally distributed, is approximately 68%.

An example of a linear transformation is

Based on the previous data, we could conclude that 90% of the students are likely to fall between what heights?

The normal distribution is

When we transform scores to a distribution that has a mean of 50 and a standard deviation of 10, those scores are called

The height of students in a dormitory is normally distributed with a mean of 68 inches and a standard deviation of 3 inches. Draw the distribution.

The difference between the histogram of 175 behavior problem scores and a normal distribution is

If a population of behavior problem scores is reasonably approximated by a normal distribution, we would expect that the X axis would

The text discussed setting "probable limits" on an observation. These limits are those which have a

Introduction

Basic Concepts

Displaying Data

Measures of Central Tendency

Measures of Variability

Basic Concepts of Probability

Sampling Distributions and Hypothesis Testing

Correlation

Regression

Multiple Regression

Hypothesis Tests Applied to Means: One Sample

Hypothesis Tests Applied to Means: Two Related Samples

Hypothesis Tests Applied to Means: Two Independent Samples

Power

One-Way Analysis of Variance

Factorial Analysis of Variance

Repeated-Measures Analysis of Variance

Chi-Square

Nonparametric and Resampling Statistical Tests

Meta-Analysis

Filters

Exam 6: The Normal Distribution

Performing a linear transformation can make any distribution normal.

Based on the height data in the previous question: a. What percent of residents are between 65 inches and 71 inches tall? b. What percent of residents are taller than 72 inches? c. What percent of residents are shorter than 72 inches?

Which of the following is NOT always true of a normal distribution?

In a normal distribution, indicate what percent of scores fall: a. between the mean and 1 standard deviation above the mean b. between plus and minus 2 standard deviations of the mean. c. 3 standard deviations above or below the mean.

The difference between "probable limits" and "confidence limits" is that the probable limits

If the salary of assistant professors in this university is normally distributed with a mean of $45,000 and a standard deviation of $1,500, what salary would have a z score of .97?

We care a great deal about areas under the normal distribution because

Assume that your class took an exam last week and the mean and standard deviation of the exam were 85 and 5, respectively. Your instructor told you that 30 percent of the students had a score of 90 or above. You would probably

The area under a particular portion of the normal curve is equivalent to theprobability of falling within that portion of the distribution.

The probability that a student will score between plus or minus one standard deviation from the mean on an exam, assuming the scores are normally distributed, is approximately 68%.

An example of a linear transformation is

Based on the previous data, we could conclude that 90% of the students are likely to fall between what heights?

The normal distribution is

When we transform scores to a distribution that has a mean of 50 and a standard deviation of 10, those scores are called

The height of students in a dormitory is normally distributed with a mean of 68 inches and a standard deviation of 3 inches. Draw the distribution.

The difference between the histogram of 175 behavior problem scores and a normal distribution is

If a population of behavior problem scores is reasonably approximated by a normal distribution, we would expect that the X axis would

The text discussed setting "probable limits" on an observation. These limits are those which have a

Introduction

Basic Concepts

Displaying Data

Measures of Central Tendency

Measures of Variability

Basic Concepts of Probability

Sampling Distributions and Hypothesis Testing

Correlation

Regression

Multiple Regression

Hypothesis Tests Applied to Means: One Sample

Hypothesis Tests Applied to Means: Two Related Samples

Hypothesis Tests Applied to Means: Two Independent Samples

Power

One-Way Analysis of Variance

Factorial Analysis of Variance

Repeated-Measures Analysis of Variance

Chi-Square

Nonparametric and Resampling Statistical Tests

Meta-Analysis

Filters