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

2. Selecting analysis and statistical techniques
De Vaus p133

3. Methods of analysis (De Vaus, 134)

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

5. 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

6. 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

7. 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