stats101
0.1
Contents:
Introduction
Inferring from a sample
Types of samples
Description and inference
Units of observation
Data sources
Software
Data structure
Tutorial data
Levels of measurement
Nominal
Ordinal
Interval
Ratio
Discrete and continuous data
Central tendency
Mode
Median
Mean
Measures of spread
Range
Inter–quartile range
Variance
Standard deviation
Standard error and confidence intervals
Comparing means and confidence intervals
Normal distribution
Skewness
Kurtosis
Hypothesis testing
Null hypothesis
Errors interpreting the results
Directional tests
Chi–squared test
Test statistic
Degrees of freedom
p
value
Assumptions
Odds ratio
Correlation
Pearson’s correlation coefficient,
\(r\)
Assumptions
Spearman’s
\(\rho\)
Kendall’s
\(\tau\)
Comparing two independent groups
\(t\)
–test
Assumptions
Mann–Whitney U
Dependent groups
Comparing three or more means
Example
Assumptions
Equality of variance
ANOVA
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stats101
¶
Contents:
Introduction
Inferring from a sample
Types of samples
Description and inference
Units of observation
Data sources
Software
Data structure
Tutorial data
Levels of measurement
Nominal
Ordinal
Interval
Ratio
Central tendency
Mode
Median
Mean
Measures of spread
Range
Inter–quartile range
Variance
Standard deviation
Standard error and confidence intervals
Comparing means and confidence intervals
Normal distribution
Skewness
Kurtosis
Hypothesis testing
Null hypothesis
Errors interpreting the results
Directional tests
Chi–squared test
Test statistic
Degrees of freedom
p
value
Assumptions
Odds ratio
Correlation
Pearson’s correlation coefficient,
\(r\)
Spearman’s
\(\rho\)
Kendall’s
\(\tau\)
Comparing two independent groups
\(t\)
–test
Mann–Whitney U
Dependent groups
Comparing three or more means
Example
Assumptions
Equality of variance
ANOVA
Indices and tables
¶
Index
Module Index
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