Free Printable AP Statistics Vocab and Notations

1.

sample mean

a)

$\overline{x}$

b)

μ

c)

σ

d)

p̂

e)

n

2.

population mean

a)

$\overline{x}$

b)

μ

c)

p

d)

p̂

e)

n

3.

sample standard deviation

a)

s

b)

$\overline{x}$

c)

σ

d)

p̂

e)

μ

4.

population standard deviation

a)

s

b)

$\overline{x}$

c)

σ

d)

p̂

e)

µ

5.

sample proportion

a)

s

b)

$\overline{x}$

c)

p

d)

p̂

e)

µ

6.

Sample Size

a)

s

b)

n

c)

p

d)

p̂

e)

µ

7.

Population Size

a)

s

b)

N

c)

P

d)

p̂

e)

µ

8.

population proportion

a)

s

b)

$\overline{x}$

c)

p

d)

p̂

e)

µ

9.

sample variance

a)

s

b)

$s^{2\ }$

c)

σ

d)

$\sigma^2$

e)

$\mu^2$

10.

population variance

a)

s

b)

$s^{2\ }$

c)

σ

d)

$\sigma^2$

e)

$\mu^2$

11.

A ____________ variable is one that takes on numerical values.

Examples: age, weight, salary, GPA, temperature, etc.

a)

categorical

b)

random

c)

minimum

d)

quantitative

e)

simple

12.

A ________ variable is one one that represents characteristics or qualities rather than numerical value

Examples: dog breed, hair color, high school attended, political affiliation, etc.

a)

categorical

b)

random

c)

minimum

d)

quantitative

e)

simple

13.

The lowest value

a)

maximum

b)

minimum

c)

Q1

d)

Q3

e)

IQR

14.

The median of the lower half of the values.

a)

maximum

b)

minimum

c)

Q1

d)

Q3

e)

IQR

15.

The median of the upper half of the values.

a)

maximum

b)

minimum

c)

Q1

d)

Q3

e)

IQR

16.

Q3-Q1

a)

maximum

b)

minimum

c)

Q1

d)

Q3

e)

IQR

17.

Maximum-Minimum

a)

range

b)

median

c)

mode

d)

mean

e)

IQR

18.

The arithmetic average of the values.

a)

range

b)

median

c)

mode

d)

mean

e)

IQR

19.

The middle value.

a)

range

b)

median

c)

mode

d)

mean

e)

IQR

20.

The value or values that occur most often.

a)

range

b)

median

c)

mode

d)

mean

e)

IQR

21.

Values that are more than 1.5 IQR’s above Q3 or 1.5 IQR’s below Q1.

a)

gaps

b)

standard deviation

c)

variance

d)

mean

e)

outliers

22.

The square root of the variance. It describes the spread of values in the model.

a)

expected value

b)

standard deviation

c)

mean

d)

observed value

e)

outliers

23.

Which can you use to describe the center of a distribution of data?

a)

range

b)

mean

c)

median

d)

standard deviation

e)

variance

24.

Which can you use to describe the shape of a distribution of data?

a)

symmetric

b)

skewed

c)

bell-shaped

d)

unimodal

e)

bimodal

25.

Which can you use to describe the spread of a distribution of data?

a)

variance

b)

IQR

c)

range

d)

standard deviation

e)

unimodal

26.

A relationship between two variables that results in them being statistically dependent.

a)

Correlation

b)

Confounding

c)

Linear Regression

d)

Residuals

e)

Association

27.

A measure of the strength and direction of the linear relationship between two quantitative variables.

a)

Correlation

b)

Confounding

c)

Linear Regression

d)

Residuals

e)

Association

28.

When we are unsure which variable is causing an effect.

a)

Correlation

b)

Confounding

c)

Linear Regression

d)

Residuals

e)

Association

29.

The differences between observed and predicted values.

a)

Correlation

b)

Confounding

c)

Linear Regression

d)

Residuals

e)

Association

30.

Correlation Coefficient

a)

c

b)

$\overline{x}$

c)

$r$

d)

$r^2$

e)

μ

31.

Coefficient of Determination

a)

c

b)

$\overline{x}$

c)

$r$

d)

$r^2$

e)

μ

32.

Types of Regression Models

a)

Power

b)

Linear

c)

Logarithmic

d)

Quadratic

e)

Exponential

33.

A sampling approach in which entire groups are chosen at random.

a)

Cluster Sample

b)

Systematic Sample

c)

Stratified Random Sample

d)

Simple Random Sample

e)

Convenience Sample

34.

A sample of individuals who are available.

a)

Cluster Sample

b)

Systematic Sample

c)

Stratified Random Sample

d)

Simple Random Sample

e)

Convenience Sample

35.

A sample of size 𝑛 in which each set of 𝑛 elements has an equal chance of being selected.

a)

Cluster Sample

b)

Systematic Sample

c)

Stratified Random Sample

d)

Simple Random Sample

e)

Convenience Sample

36.

The population is divided into subgroups and random samples are taken from each subgroup.

a)

Cluster Sample

b)

Systematic Sample

c)

Stratified Random Sample

d)

Simple Random Sample

e)

Convenience Sample

37.

Every 10th person is chosen.

a)

Cluster Sample

b)

Systematic Sample

c)

Stratified Random Sample

d)

Simple Random Sample

e)

Convenience Sample

38.

Occurs when sample participants are self-selected volunteers.

a)

Undercoverage Bias

b)

Response Bias

c)

Time Bias

d)

Voluntary Response Bias

e)

Nonresponse Bias

39.

Occurs when some members of the population are inadequately covered in a sample.

a)

Undercoverage Bias

b)

Response Bias

c)

Time Bias

d)

Voluntary Response Bias

e)

Nonresponse Bias

40.

Occurs when those unwilling or unable to take part in a research study are different from those who do.

a)

Undercoverage Bias

b)

Response Bias

c)

Time Bias

d)

Voluntary Response Bias

e)

Nonresponse Bias

41.

A descriptive measure (using a numerical value) of the population.

a)

Sample

b)

Statistic

c)

Random

d)

Parameter

e)

Variable

42.

A descriptive measure (using a numerical value) of a sample.

a)

Sample

b)

Statistic

c)

Random

d)

Parameter

e)

Variable

43.

What is the shape of the distribution?

a)

Skewed Left

b)

Skewed Right

c)

Symmetric

d)

Bimodal

44.

Type of Data arrangement

a)

Symmetrical

b)

Hairline

c)

Skewed Right

d)

Skewed Left

45.

a)

Skewed Right

b)

Skewed Left

c)

Uniform

d)

Symmetric

46.

a)

Skewed Right

b)

Skewed Left

c)

Uniform

d)

Symmetric

47.

How is the graph distributed?

a)

Normally

b)

Skewed to the Left

c)

Skewed to the Right

d)

Uniform

48.

How is the graph distributed?

a)

Normally

b)

Skewed to the Left

c)

Skewed to the Right

d)

Uniform

49.

Population Parameters

a)

$\overline{x},\ \mu,\ s,\ \sigma,\ \beta$

b)

$\mu,\ \sigma,\ \rho,\ \beta,\ P$

c)

$\overline{x},\ s,\ r,\ b,\ _p^{\wedge}$

d)

$\mu,\ \sigma,\ \rho,\ b,\ S$

e)

$\mu,\ \sigma,\ r,\ b,\ _p^{\wedge}$

50.

Sample Statistics

a)

$\overline{x},\ \mu,\ s,\ \sigma,\ \beta$

b)

$\mu,\ \sigma,\ \rho,\ \beta,\ P$

c)

$\overline{x},\ s,\ r,\ b,\ _p^{\wedge}$

d)

$\mu,\ \sigma,\ \rho,\ b,\ S$

e)

$\mu,\ \sigma,\ r,\ b,\ _p^{\wedge}$

51.

A random variable that can take any numeric value within a range of values.

a)

Simple Random Variable

b)

Bimodal Random Variable

c)

Discrete Random Variable

d)

Quantitative Random Variable

e)

Continuous Random Variable

52.

A random variable that can take a number of distinct outcomes.

a)

Simple Random Variable

b)

Bimodal Random Variable

c)

Discrete Random Variable

d)

Quantitative Random Variable

e)

Continuous Random Variable

53.

A model that tells us how many n trials are required to achieve the first success.

a)

Binomial Probability Model

b)

Quantitative Probability Model

c)

Random Probability Model

d)

Geometric Probability Model

e)

Arithmetic Probablity Model

54.

A model that tells us the number of successes in 𝑛 trials.

a)

Binomial Probability Model

b)

Quantitative Probability Model

c)

Random Probability Model

d)

Geometric Probability Model

e)

Arithmetic Probablity Model

55.

As the size of the sample n increases, the model becomes more Normal.

a)

Law of Large Numbers

b)

Central Limit Theorem

c)

10% Condition

d)

Binomial Rule

e)

Sampling Variability

56.

As a sample size increases, the mean of the sample will more closely resemble the mean of the population.

a)

Law of Large Numbers

b)

Central Limit Theorem

c)

10% Condition

d)

Binomial Rule

e)

Sampling Variability

57.

The statement or claim being made (which we are testing).

a)

Null Hypothesis

b)

Alternative Hypothesis

c)

Parameter

d)

Statistic

e)

Variable

58.

Statement that we are trying to prove and which is accepted if the claimed statement is rejected.

a)

Null Hypothesis

b)

Alternative Hypothesis

c)

Parameter

d)

Statistic

e)

Variable

59.

The probability that the observed statistic value (or a more extreme value) could occur in a sampling distribution.

a)

power

b)

critical value

c)

t statistic

d)

z statistic

e)

p-value

60.

The probability that the test correctly rejects a false null hypothesis.

a)

power

b)

critical value

c)

t statistic

d)

z statistic

e)

p-value

61.

Fail to reject the null hypothesis when it is false.

a)

Type I Error

b)

Type II Error

c)

Power

d)

Bias

e)

Hypothesis

62.

Fail to reject the null hypothesis when the alternative is true.

a)

Type I Error

b)

Type II Error

c)

Power

d)

Bias

e)

Hypothesis

63.

Reject the null hypothesis when it was true.

a)

Type I Error

b)

Type II Error

c)

Power

d)

Bias

e)

Hypothesis

AP Statistics Vocab and Notations

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