Deck 7: Statistics and Parameters

Question 1

If the names of all the students at Omega University were placed in a fishbowl, and the researcher selected out 10% of the names, the resulting sample would be

A) biased
B) random
C) stratified
D) far too small for meaningful analysis

Answer 1

B

Question 2

Any value which is based on having measured a sample is called

A) a parameter
B) a statistic
C) an infinite measure
D) biased

Answer 2

B

Question 3

Omega University has a total student enrollment of 6000, and all 6000 students were tested for IQ. The mean IQ for the group was 115. This value of 115 constitutes a

A) statistic
B) population
C) sample
D) parameter

Answer 3

D

Question 4

The size of a given population may be

A) finite
B) infinite
C) determined on the basis of the total number of observations sharing a given trait
D) all of these

Question 5

When a group is selected from a population on the basis of sharing the same percentages of trait characteristics as are known to exist in the population, then the group so selected would constitute

A) a random sample
B) a stratified sample
C) a biased sample
D) a sampling distribution

Question 6

If every 10th student entering the college library on a Tuesday afternoon were selected for testing, the group thus selected would constitute

A) a sample
B) a random sample
C) a quota sample
D) a statistic

Question 7

If Omega University had a total student enrollment of 600, and 5999 of these students were selected for testing, the group being test would constitute

A) sample
B) a population
C) a parameter
D) a statistic

Question 8

The techniques of inferential statistics are designed to yield

A) eternal truth
B) data descriptions
C) probability estimates
D) all of these

Question 9

It is assumed that random sample

A) must contain bias
B) is too much a matter of chance to be dependable
C) is only valid when used for description purposes
D) will probably be representative of the population

Question 10

Populations are to parameters as samples are to

A) populations
B) statistics
C) infinite measures
D) finite measures

Question 11

When a sample mean is greater than the true, population mean, the resulting difference is called

A) bias
B) statistical regression
C) measurement transformation
D) sampling error

Question 12

Random sampling occurs when

A) the sample is selected from a single population
B) a random choice determines the first subject to be selected
C) the sample is selected from an infinite population
D) all members of the population have an equal chance of being selected

Question 13

Any value which is based on having measured the entire population is called

A) a parameter
B) a statistic
C) a finite measure
D) none of these

Question 14

If the mean IQ of all Omega University students was equal to 115, and a small sample of students was selected from the population whose mean IQ was 120, then this difference of 5 points would equal

A) parameter
B) the statistic
C) the sampling error
D) the deviation quartile

Question 15

Predicting the characteristics of an entire group, after having measured a small group, is the major goal of

A) probability theory
B) descriptive statistics
C) measurement theory
D) inferential statistics

Question 16

When sample means are consistently lower than the true, population mean, the result is called

A) biased
B) statistical regression
C) measurement transformation
D) sampling error

Question 17

An entire group of persons, things or events having at least one trait in common defines the

A) population
B) sample
C) statistic
D) measurement scale

Question 18

If 10 Omega University students were selected out of the total population of 6000, and median IQ for this small group equaled 118, then this value of 118 would constitute a

A) statistic
B) population
C) sample
D) parameter

Question 19

In order to make accurate population estimates, the sample must be

A) very large
B) representative of the population
C) manipulated by the experimenter
D) free of any possible sampling error

Question 20

When the population mean differs from the sample mean, the result is called

A) bias
B) statistical regression
C) measurement transformation
D) sampling error

Question 21

Whenever the sampling error is consistently in one direction, the result is

A) a negative sampling error
B) a positive sampling error
C) a population exclusion
D) bias

Question 22

When graphing the sampling distribution of means, the various sample means are represented on

A) the abscissa
B) the ordinate
C) the Y axis
D) none of these

Question 23

The sample selected by the Literacy Digest in 1936 was

A) far too small to be accurate
B) overly represented by affluent voters
C) overly represented by Democrats
D) truly random

Question 24

By definition, one can never obtain a statistic unless

A) the entire population has been measured
B) a random sample has been measured
C) a quota sample has been measured
D) none of these, since a statistic refers to a measure of any type of sample

Question 25

The sum total of all registered voters in Canada represents

A) the population of potential Canadian voters
B) a parameter
C) statistic
D) sampling error

Question 26

Any sample which contains fewer than 50% of the total population

A) must be biased
B) must be non-random
C) must be inaccurate
D) none of these

Question 27

Sampling error is assumed to result

A) when any sample is selected
B) only when a non-representative sample is selected
C) only when a biased sample is selected
D) only when the researcher makes a mistake

Question 28

The sampling distribution of means assumes normality only when

A) all samples are randomly selected
B) all samples have been selected from a single population
C) the samples represent groups of sufficient size
D) all of these

Question 29

The mean of the entire distribution of sample means represents

A) a parameter
B) a statistic
C) the sampling error
D) none of these

Question 30

When the sampling distribution of means is randomly selected from an entire population of individual scores, the highest and lowest individual scores

A) become lost through averaging
B) must be arbitrarily eliminated before the sampling distribution becomes available
C) assume the characteristics of parameters
D) produce a bimodal distribution

Question 31

When a group is truly selected randomly from a population, the probability of its mean value being higher than the parameter mean is

A) 0.00
B) .50
C) 1.00
D) .33

Question 32

The normal, expected difference between a statistic and a parameter is called

A) sampling error
B) bias
C) controlled randomization
D) none of these, since statistics and parameters may never differ

Question 33

The reason the Literary Digest's 1936 election poll was so inaccurate, was that

A) the sample was too small
B) it contained sampling error
C) the sample was biased
D) the wrong statistical tests were employed for extrapolating to the

Question 34

The range of values for the sampling distribution of means

A) is larger than the range of the underlying individual scores
B) is identical to the range of the underlying individual scores
C) is smaller than the range of the underlying individual scores
D) is always equal to 30 or higher

Question 35

Each point on the abscissa of the distribution of sample means represents

A) a parameter
B) a statistic
C) the sampling error
D) the population error

Question 36

When graphing the sampling distribution of means, the ordinate represents

A) sample mean
B) a population mean
C) a statistical mean
D) the frequency of occurrence

Question 37

The Central Limit Theorem states that the sampling distribution of means is

A) only available by inference
B) only available when sample sizes are less than 10
C) only available when the very high and very low means have been eliminated
D) approximately normal in shape

Question 38

The problem with the Gallup poll of 1948 (when Dewey was predicted to beat Truman) was that

A) the polling ended too soon
B) the "undecideds" were split 50/50
C) many of the "undecideds" had, in fact, already made up their minds
D) all of these

Question 39

The probability of obtaining a random sample mean which is lower than the population mean is

A) 1.00
B) 0
C) .50
D) none of these, since a sample mean can never be lower than a population

Question 40

A biased sample can never be

A) selected from a single population
B) selected when the parameters are known
C) selected when the entire population is available
D) representative of the population

Question 41

The z test may be used to determine

A) if the sample is representative of a known population
B) if a sample contains bias
C) the exact amount of sampling error contained in the parameter mean
D) the amount of sampling error contained in the population's standard

Question 42

In order to calculate the z test, one must know

A) the sample's true standard deviation
B) the amount of sampling error present
C) the parameter mean, the parameter standard deviation and the sample mean
D) the exact amount of bias contained in the sample

Question 43

A statistic always refers to a sample measure.

Question 44

When the standard deviation of the entire distribution of random sample means had been calculated, the resulting value is called

A) the deviation score
B) the parameter mean
C) the standard error of the mean
D) sampling error

Question 45

When all possible samples have been randomly selected from a single population, the standard deviation of the resulting distribution of means is called

A) the "true" standard deviation of the sample's individual scores
B) the "true" standard deviation of the population's individual scores
C) the standard error of the mean
D) sample variance plus error variance

Question 46

Each and every time a sample is selected, sampling error must be assumed.

Question 47

Statistic is to sample as parameter is to population.

Question 48

Bias is the difference between the sample measure and the population measure.

Question 49

The major error in inferential statistics is to commit the "sampling error".

Question 50

The fact that the distribution of random sample means is assumed to approximate normality is expressed in

A) the Gaussian Law
B) Pascal's triangle
C) the Central Limit theorem
D) none of these, since the premise is false

Question 51

When sampling error is constant and in one direction, the sampling must be biased.

Question 52

With true random sampling, every observation in the population has an equal chance of being selected.

Question 53

The Central Limit theorem states the exact probability value of estimating the true mean.

Question 54

A population may never share more than one common trait.

Question 55

The standard error of the mean must equal

A) the standard deviation of the sample's distribution of individual scores
B) the standard deviation of the entire population's distribution of individual scores
C) the "average" of the sample's distribution of individual scores and the population's distribution of individual scores
D) the standard deviation of the entire sampling distribution of means

Question 56

The probability estimates provided by inferential statistics are only necessary when

A) the population values are unknown
B) the parameters are given
C) the population values are provided
D) none of these

Question 57

True population may never be infinite.

Question 58

When comparing the size of the standard error of the mean with the size of the standard deviation of the underlying distribution of individual scores,

A) the standard error of the mean is always larger
B) the standard error of the mean is always smaller
C) the standard error of the mean is sometimes larger and sometimes smaller, depending on the sample size
D) none of these

Question 59

One measure of the overall sampling error in the entire distribution of sample means is the

A) standard error of the mean
B) population mean
C) population median
D) sample's true amount of bias

Question 60

The z test assumes that

A) the sample mean is equal to the population mean
B) the standard deviation of the sample scores is equal to the standard deviation of the distribution of sample means is normal
C) the distribution of sample means is normal
D) none of these, since the z test is "assumption free"

Question 61

The z test assumes that the sample's standard deviation equals the standard error of the mean.

Question 62

With a known population mean of 1500, and a known standard error of the mean of 42.50, what is the probability of selecting at random a sample whose mean is 1450 or less?

Question 63

With a known population mean of 50 and a known standard error of the mean of 4.00, what is the probability of selecting at random a sample whose mean is 52 or greater?

Question 64

With a known population mean of 100, and a known standard error of the mean of 7.5, what is the probability of selecting at random a sample whose mean is equal to 110 or greater?

Question 65

With a normal distribution, if the standard deviation in the population of individual verbal SAT scores is 100, then the Range should approximate_________

Question 66

The Central Limit theorem states that the sampling distribution of means is normal in shape.

Question 67

The standard deviation of the population of individual scores is 22.50. A given random sample of 100 scores produces a mean of 210. Calculate the standard error of the mean.

Question 68

The null hypothesis for the z test, since it is based on chance, must always be accepted.

Question 69

The z test assumes that the sampling distribution of means is normal.

Question 70

With a known population mean of 75 and a known standard error of the mean of 5.00, what is the probability of selecting at random a sample whose mean is 70 or less?

Question 71

The z test assumes knowledge of the two population parameters, the mean and the standard deviation.

Question 72

The Central Limit theorem only applies when the distribution of individual sample scores is normal.

Question 73

The standard deviation of the population of adult female height scores is 3 inches. A random sample of 50 women yields a mean height of 64 inches. Calculate the standard error of the mean. 95

Question 74

When samples are selected randomly, they are assumed to be representative of the population.

Question 75

The standard deviation of the population of individual scores is 15. A random sample of 10 scores yields a mean of 100. Calculate the standard error of the mean.

Question 76

The z test draws a comparison between the sample means and the known population mean.

Question 77

Stratified sampling refers to the actual number of different samples being selected from a single population.

Question 78

With a known population mean of 10 and a known standard error of the mean of 1.47, what is the probability of selecting at random a sample whose mean is 8.50 or less?

Question 79

For the z test, the null hypothesis states that the sample and parameter means are equal.

Question 80

With a known population mean of 68 and a known standard error of the mean of 2.58, what is the probability of selecting at random a sample whose mean is 70 or greater?