Notes on Statistical Analysis

Descriptive Statistics

• Used to describe data.

• Key measures include mean, median, and mode, which serve as central values.

• Standard deviation indicates the distance of data points from the mean.

Inferential Statistics

• Used to find significant differences and prove assumptions through probability.

• P-value is crucial for proving assumptions.

• Aims to generalize findings from a sample to a larger population.

Significant Difference Testing

• Potential significant difference testing is used when the number of respondents is limited.

• Statistical treatment compares significant differences between groups.

• Shapiro-Wilk normality test determines data normality; if the p-value is less than 0.05, the data is not normal, and the null hypothesis is rejected.

P-Value Significance

• P-value represents probability; a p-value of 0.05 is a common threshold.

• If the p-value < 0.05, reject the null hypothesis, indicating a significant difference.

• If the p-value > 0.05, fail to reject the null hypothesis, indicating no significant difference.

Hypothesis Testing

• Null hypothesis (H0): There is no significant difference.

• Alternative hypothesis: There is a significant difference.

• Reject H0 if p-value is less than 0.05.

Statistical Statements

• Descriptive statistics describe data by presenting averages or means.

• Inferential statistics use probability to make assumptions and test hypotheses.

Independent Sample T-Test

• Used to test for significant differences between two independent groups.

Key P-Value Threshold

• P-value threshold is often set at 0.05, corresponding to a 95% confidence level.