# Statistics Hardest Practice Quiz! Trivia Test

44 Questions | Total Attempts: 265  Settings  .

Related Topics
• 1.
Statistics is the study of _____________.
• A.

Testing and interpreting statistical hypotheses about a relationship

• B.

Mathematical analysis using samples instead of populations

• C.

Summarizing, analyzing, or drawing inferences about a relationship

• D.

Inferring something about a population from a sample

• 2.
Which of the following is not a variable?
• A.

Personal fantasies

• B.

The final score of the Yankees game on 10/17/09

• C.

Body temperatures of people who are NOT sick

• D.

Age

• 3.
Why is it important to record demographics?
• A.

Different populations act differently

• B.

The IRB mandates it for studies conducted

• C.

There's no way to tell if you're measuring a consistent estimator

• D.

There's no way to tell if you're measuring a sufficient estimator

• 4.
How is an ordinal variable more detailed than a nominal variable?
• A.

0 means the total absence of the variable

• B.

The categories are qualitative groupings

• C.

The categories possess value

• D.

The distance between the categories is equal

• 5.
How is a ratio variable more detailed than an interval variable?
• A.

0 means the total absence of the variable

• B.

The categories are qualitative groupings

• C.

The categories possess value

• D.

The distance between the categories is equal

• 6.
What kind of variable is a person's height?
• A.

Discrete

• B.

Continuous

• C.

Ungrouped

• D.

Grouped

• 7.
What kind of frequency distribution is the above?
• A.

Ungrouped frequency distribution

• B.

Grouped frequency distribution

• C.

Relative frequency distribution

• D.

Cumulative frequency distribution

• 8.
What kind of frequency distribution is the above?
• A.

Ungrouped frequency distribution

• B.

Grouped frequency distribution

• C.

Relative frequency distribution

• D.

Cumulative frequency distribution

• 9.
What would a stem and leaf plot look like for:10, 11, 13, 13, 21, 31, 36
• A.

10, 11, 13, 13 21 31, 36

• B.

1 | 0, 1, 3, 3 2 | 1 3 | 1, 6

• C.

10s X X X X 20s X 30s XX

• D.

10s+ XXXX 20s+ XXXXX 30s+ XXXXXXX

• 10.
In a positively skewed distribution, ____________.
• A.

The bulk of the scores are on the left side

• B.

The bulk of the scores are on the right side

• 11.
Kurtosis is the measure of ______________.
• A.

The amount that the peak is shifted positively or negatively

• B.

The shape of the distribution's peak

• C.

Whether the distribution has enough scores (N)

• D.

The cumulative relative frequency

• 12.
B would be described as being ___________.
• A.

Mezokurtic

• B.

Hypokurtic

• C.

Platykurtic

• D.

Leptokurtic

• 13.
A would be described as _______________.
• A.

Mezokurtic

• B.

Hypokurtic

• C.

Platykurtic

• D.

Leptokurtic

• 14.
The mode is an especially poor choice of measuring central tendency when ___________.
• A.

The distribution is bimodal

• B.

The distribution is heavily positively skewed

• C.

The distribution is leptokurtic

• D.

The distribution is a normal curve

• 15.
The median is a better choice of measuring central tendency than the mean when _____________.
• A.

The distribution is bimodal

• B.

The distribution is heavily positively skewed

• C.

The distribution is leptokurtic

• D.

The distribution is a normal curve

• 16.
The sum of deviations [ Summation (X-Xbar)] is always equal to ____________.
• A.

The mean

• B.

The median

• C.

0

• D.

It's possible for it to be different every time

• 17.
In which of the following situations would just providing the mean without also providing variability be bad?
• A.

Giving the mean number of meters a guided missile lands from the target but not the variability

• B.

Giving the mean amount of IQ increase seen in children in a single year but not the variability

• C.

Giving the mean number of crimes committed by a demographic but not the variability

• D.

All of the above

• 18.
___________ is the measure of variability most affected by outlier scores.
• A.

Range

• B.

Interquartile range

• C.

Variance

• D.

Standard deviation

• 19.
When calculating variance for a sample, we use the following formula:Sum of Squares / (N-1)What benefit is there to subtracting 1?
• A.

Makes sure studies cannot be done with case studies (N=1)

• B.

The lower the number of participants, the more the -1 increases sample variability

• C.

If we don't subtract 1, the sum of deviations won't equal 0

• D.

Subtracting 1 makes the distribution appear more normal like

• 20.
Why do we use standard deviation instead of variance?
• A.

Standard deviation takes into account the N of the sample

• B.

Standard deviation is less susceptible to outlier scores than the variance.

• C.

Standard deviation has the same scale of measurement as the mean

• D.

Standard deviation takes into account degrees of freedom of the sample

• 21.
Which of the following is not a requirement of a perfect normal distribution?
• A.

Identical mean, median, and mode

• B.

Asymptotic distribution

• C.

Has a standard deviation of 1.

• D.

Has range of negative infinity to positive infinity

• 22.
• A.

Standard deviation = 1

• B.

Mean = 0

• C.

Easier to compare values across variables

• D.

Converting scores to a standard normal distribution turns the distribution into a perfect normal distribution

• 23.
If I were to look at the scores on a test from a single classroom and assume the findings apply to the whole school, I would be using ___________.
• A.

Descriptive statistics

• B.

Inferential statistics

• C.

Sample statistics

• D.

Population statistics

• 24.
Which of the following is true?
• A.

All consistent estimators are unbiased estimators

• B.

All unbiased estimators are consistent estimators

• C.

Not all biased estimators are consistent estimators

• D.

Consistent estimators are never biased estimators

• 25.
Which of these is the crappiest type of sampling?
• A.

Snowball sampling

• B.

Convenience sampling

• C.

Random sampling

• D.

Stratified random sampling

• 26.
Why isn't random sampling as good as stratified random sampling?
• A.

Random sampling does not give everyone an equal chance of participation

• B.

Random sampling is not independent

• C.

In random sampling you run the risk of asking both the old grandma at the grocery store as well as the grandpa she's with

• D.

Random sampling doesn't guarantee representativeness

• 27.
The sampling distribution of a normally distributed variable with N = infinity would be...
• A.

Mezokurtic

• B.

Platykurtic

• C.

Leptokurtic

• D.

Random

• 28.
The Law of Large Numbers states ___________.
• A.

Point estimators become increasingly less stable at large numbers

• B.

The larger the sample you take, the more likely you are to come close to the population mean

• C.

A sample is normally distributed when adding more people won't bring you any closer to the mean

• D.

Central limit theorom does not apply to significantly high values of Z

• 29.
What is the estimated standard error of the mean?
• A.

The average distance away a score is from the mean

• B.

The average distance away a sample mean is from the population mean

• C.

The square root of the population variance

• D.

The likelihood that the sample mean is within 1 standard deviation of the population mean

• 30.
Why might a WISC administrator not refer to an IQ of 89 as below average?
• A.

Because the FSIQ is an imperfect point estimator and therefore we really have no idea what the real score is

• B.

Because the FSIQ has not been found to be statistically valid or reliable

• C.

Because 42% of children score below 89 so it's really not that far below average

• D.

Because the 95% confidence interval falls between 88-96 so we're not all that certain the score is really below average

• 31.
If I tell you that you got a Z score of -2 on the WAIS, you should feel:
• A.

Alarmed

• B.

Average

• C.

Appropriately proud

• D.

Incredibly proud

• 32.
Which of the following is false about H0 and H1:
• A.

They must be mutually exclusive

• B.

They must be appropriate for the rejection criteria

• C.

There can be no overlap or exceptions

• D.

They must be all encompassing

• 33.
I'm running some screening tests to see which kids should be monitored more closely next year because the screening test indicates they're at risk for learning disorders. What might I set my alpha to?
• A.

.005

• B.

.10

• C.

.95

• D.

.995

• 34.
I'm writing software for missile-detection radar, to alert the Pentagon in case the Commies try to nuke us. What should I set my alpha to?
• A.

.005

• B.

.10

• C.

.95

• D.

.995

• 35.
__________ is when you accept the null hypothesis when it's false.
• A.

Type 1 Error

• B.

Type 2 Error

• C.

H0 Error

• D.

H1 Error

• 36.
__________ is used when you have a sample mean, estimated standard error, population mean, and N.
• A.

Independent samples t-test

• B.

Repeated measures t-test

• C.

One sample t-test

• D.

Bivariate t-test

• 37.
__________ is used when you have two sample means, two estimated standard errors, and two Ns.
• A.

Independent samples t-test

• B.

Repeated measures t-test

• C.

One sample t-test

• D.

Bivariate t-test

• 38.
_________ is used when you compare two sample means from one population.
• A.

Independent samples t-test

• B.

Repeated measures t-test

• C.

One sample t-test

• D.

Bivariate t-test

• 39.
If I'm doing a t-test and my N = 30 and I want to use 95% confidence, I should look up the t-table value at:
• A.

29 and .05

• B.

29 and .95

• C.

30 and .05

• D.

30 and .95

• 40.
If I'm doing a t-test and my N = 32, I should look up the t-table value at:
• A.

30

• B.

40

• C.

Average 30 and 40

• D.

Average 30 and 40 with 80% weight on the 30

• 41.
Independent samples t-test requires assuming all of the following except:
• A.

Each subject is randomly and independently selected from the population

• B.

Measurement is done on ratio variables

• C.

Assumption of homogeneity of variance

• D.

Scores in population form normal curve

• 42.
Repeated measures t-test eliminates one of the assumptions from independent samples t-test, which?
• A.

Each subject is randomly and independently selected from the population

• B.

Measurement is done on ratio variables

• C.

Assumption of homogeneity of variance

• D.

Scores in population form normal curve

• 43.
Say I test the effect of milk consumption on height by monitoring the height of students in a classroom where milk is supplied daily and the height of students in a classroom where milk is not supplied daily. I'm going through the steps to make a study and set my rejection parameters to t=2.045 with an alpha of .05. After I run my analysis, I discover that my independent samples t-test has returned me t=1.940.  What conclusion should I reach, and what error am I at risk of committing?
• A.

Accept null hypothesis; Type 1 Error

• B.

Accept null hypothesis; Type 2 Error

• C.

Reject null hypothesis; Type 1 Error

• D.

Reject null hypothesis; Type 2 Error

• 44.
Say I test the effect of milk consumption on height by monitoring the height of students in a classroom where milk is supplied daily and the height of students in a classroom where milk is not supplied daily. I'm going through the steps to make a study and set my rejection parameters to t=2.045 with an alpha of .05. After I run my analysis, I discover that my independent samples t-test has returned me t=1.940.  I accept the null hypothesis, therefore, what is my conclusion?
• A.

With an alpha of .05, milk consumption over the course of a year does not alter students' heights

• B.

With an alpha of .05, milk consumption over the course of a year does alter students' heights

• C.

With an alpha of .05, this study was inconclusive and it is unclear what effect milk consumption over the course of a year has on students' heights

• D.

If the t-test returned 1.940, it is an indication that the N was too low and the study should be redone