Experimental Design

Sampling design:
simple random sample,
stratified random sample,
multistage random sample

• 3.26
• 3.27
• 3.29
• 3.61
• 3.63

Relative frequency

Independence

Random variables (discrete or continuous) and
their distributions

Normal distributions

Sampling distributions and the Central Limit Theorem

Multiplication rule for independent events

Calculating means and standard deviations for discrete random variables

z-scores

normalcdf

• 1.112
• 1.115
• 1.117
• 1.127
• 1.137
• 4.21
• 4.29
• 4.36
• 4.39
• 4.51
• 4.75
• 4.77
• 4.137
• 5.45
• 5.49
• 5.55
• 5.71

Descriptive Statistics:

Mean and standard deviation

Median and quartiles

Gaps and outliers, skew

Stemplots

Histograms

Boxplots

• 1.21
• 1.26
• 1.41
• 1.56
• 1.65
• 1.79
• 1.84

Relationships:

Regression line

Correlation coefficient

Influential observations

Making scatterplots

Calculating r

Calculating the regression line

Making predictions

• 2.17
• 2.19a
• 2.23
• 2.39
• 2.45
• 2.63
• 2.87ab
• 2.138

Inferential Statistics:
(These all use the t-distribution.)

Confidence intervals for a mean or for the difference of two means;
determining sample size

Hypothesis tests for a mean or for two means

Matched-pair comparisons

TInterval

TTest

2-SampTInt

2-SampTTest

• 6.13
• 6.14
• 6.29
• 6.53
• 6.61
• 7.25
• 7.32abce
• 7.33
• 7.37
• 7.63
• 7.65

Descriptive Statistics:

Counts and relative frequency

Binomial distributions

Bar graphs and pie charts

binompdf

binomcdf

• 1.17
• 1.20
• 5.11
• 5.13
• 5.21
• 5.23ab
• 5.28
• 5.67

Relationships:

Two-way tables

Marginal distributions and conditional distributions

• 2.113
• 2.119

Inferential Statistics:

Confidence intervals for a proportion or for the difference between two proportions;
determining sample size

Hypothesis tests for a proportion or for two proportions

Chi-square tests for independence of two variables

1-PropZInt

1-PropZTest

2-PropZInt

2-PropZTest

X2-Test

• 8.15
• 8.19
• 8.22
• 8.32
• 8.47
• 8.51
• 9.11
• 9.17