Asynchronous Statistics Review - 9/21 Asynchronous Day

Scales of Measurement

• Categorical (nominal)

• Quantitative (ordinal and interval/ratio)

Categorical

Nominal Scale, used for naming/labeling variables without a quantitative value.

Numerical/Quantitative

• Ordinal - used for measuring variables that have numeric value and can be ordered or ranked.

• Interval - includes numeric values with meaningful intervals, but interval scales do not have a true zero.

• Ratio - all properties of interval scales, with a true zero that allows for meaningful comparisons of ratios.

Descriptive Statistics

Descriptive Statistics describe the sample (ex. mean, standard deviation, frequency). They are often represented with numbers or graphs.

Inferential Statistics

• Inferential Statistics is a branch of statistics that allows researchers to make conclusions or predictions about a population based on sample data. It includes methods like hypothesis testing and estimation.

• Inferential statistics employ t-tests to determine if there are significant differences between groups or to estimate population parameters. Different t-tests include Independent samples t-test and Paired samples t-test.

Independent t-test

A statistical method used to determine if there are significant differences between the means of two independent groups (different people in each condition)

Paired Samples t-test

A statistical method used to compare the means of two related groups (the same participants measured at different times or under different conditions) to determine if there is a significant difference between them (the two things being compared are linked)

Pearson Correlation (r-statistic)

• Ranges from -1 to 1

• Two variables, both interval/ratio

• Interpretation depends on strength/direction

ANOVA (Analysis of Variance)

• One way ANOVA - three or more nominal groups as a predictor, interval/ratio DV (can be within groups or between groups)

• Two way ANOVA - two nominal predictor variables, interval/ratio DV (each predictor variable can be within groups or between groups)

Chi-Squared Test

• Comparing the frequency of two nominal variables (ex how many commuters vs how many residents)

• Associated statistic - frequencies

Between-Groups Design

A research design where participants are assigned to different groups, each receiving a different condition, allowing comparison of outcomes between these independent groups.

Within-Groups Design

A research design in which participants are exposed to all conditions, allowing for comparisons of outcomes within the same group across different conditions.