Summarising and presenting data - Univariate analysis continued LIS 570 Summarising and presenting data - Univariate analysis continued Bivariate analysis

Selecting analysis and statistical techniques De Vaus p133

Methods of analysis (De Vaus, 134)

Summary Inferential statistics for univariate analysis Bivariate analysis crosstabulation the character of relationships - strength, direction, nature correlation

Inferential statistics - univariate analysis Interval estimates - interval variables estimating how accurate the sample mean is based on random sampling and probability theory Standard error of the mean (Sm) Sm = s N Standard deviation Total number in the sample

Standard Error Probability theory for 95% of samples, the population mean will be within + or - two standard error units of the sample mean this range is called the confidence interval standard error is a function of sample size to reduce the confidence interval, increase the sample size

Inference for non-interval variables For nominal and ordinal data Variable must have only two categories may have to combine categories to achieve this SB = PQ N P = the % in one category of the variable Q = the % in the other category of the variable Total number in the sample Standard error for binominal distribution