1. Introducing Communication Research 2e © 2014 SAGE Publications Chapter Seven Generalizing From Research Results: Inferential Statistics

2. Key Concepts Statistical significance. Normal distribution. Random sampling. Confidence level & confidence interval. Parametric vs. non-parametric. t-test, ANOVA & correlation. Type I and Type II error. Introducing Communication Research 2e © 2014 SAGE Publications

3. Inferential Statistics Inferential statistics help us – Estimate the probability that a sample represents the population it came from. Decide whether groups differ significantly on a variable. Decide whether there are significant relationships among or between variables. Introducing Communication Research 2e © 2014 SAGE Publications

4. Inferential Statistics and the Normal Curve Inferential statistics assume that the values of a variable in a population are normally distributed. Assuming a normal distribution of values in a population, we can calculate the probability that a sample of that population has captured its characteristics. Introducing Communication Research 2e © 2014 SAGE Publications

5. The Normal Curve and Standard Deviation In a normal distribution – 68% of values occur plus or minus one standard deviation (SD) from the mean. 95% of its values occur plus or minus two SDs from the mean. 99.7% of its values occur plus or minus three SDs from the mean. Introducing Communication Research 2e © 2014 SAGE Publications

6. Statistical Significance Significance means that there is a better than random chance that a relationship exists. Introducing Communication Research 2e © 2014 SAGE Publications

7. Confidence Interval and Confidence Level Confidence Interval The possible range of values for a variable in a population, calculated from a sample of the population. Confidence Level The probability of a calculated value occurring. Example – There is a 95% probability that the mean lies between 0.98 and 10.42. Introducing Communication Research 2e © 2014 SAGE Publications

8. For a Sample The distribution of the sample results is called the sampling distribution. The standard deviation is called the standard error. Standard error decreases as sample size increases. Introducing Communication Research 2e © 2014 SAGE Publications

9. Parametric vs Non-parametric Statistics Parametric Statistics Used where we can assume a normal distribution of values in the population. Non-Parametric Statistics Used where we cannot assume a normal distribution of values in the population. Introducing Communication Research 2e © 2014 SAGE Publications

10. Standard Deviation A measure of the extent to which a set of scores vary on either side of their mean value. The square root of variance. For a sample, standard deviation is referred to as the standard error. Introducing Communication Research 2e © 2014 SAGE Publications

11. t-Test Compares mean scores from two groups to determine the probability the groups are different. t-test for independent samples - Used where the groups are different. t-test for dependent samples - Used where the groups are the same. The higher the t-value, the lower the probability it will occur. Introducing Communication Research 2e © 2014 SAGE Publications

12. Degrees of Freedom A measure of “room to move.” ▫How many ways could our data be combined and still produce the same values for a statistic? Introducing Communication Research 2e © 2014 SAGE Publications

13. One and Two-tailed Tests One-tailed Test Presupposes that a difference between groups will be directional for example, that a value for group A will be higher than for group B. Two-tailed Test Presupposes that the difference will be non- directional for example, group A and group B simply differ; either group could score higher or lower. Introducing Communication Research 2e © 2014 SAGE Publications

14. Analysis of Variance (ANOVA) Assesses the probability of difference among two or more groups. Compares the variance within groups with the variance between groups. One-way ANOVA compares one variable across more two or more groups. Multiple Analysis of Variance (MANOVA) assesses relationships among multiple variables across two or more groups. Introducing Communication Research 2e © 2014 SAGE Publications

15. Correlation and Regression Correlation – a measure of the strength of association among and between variables. Correlation coefficient - expresses the strength of association between variables. Regression - predicts a value for one variable given a value for another variable. Relationships between variables may plot out as linear or curvilinear Introducing Communication Research 2e © 2014 SAGE Publications

16. Type I and Type II Error Accept null hypothesisReject null hypothesis Null hypothesis is true in the wider population. No problem.Type I Error. Decided wrongly that there was a significant result. Null hypothesis is false in the wider population. Type II Error. Decided wrongly that there was no significant result. No problem. Introducing Communication Research 2e © 2014 SAGE Publications

17. Chapter Summary Inferential statistics assess – ▫the probability that a sample represents a population ▫the strength of relationships among variables ▫the strength of differences among groups. t-test – compares values of a continuous variable for two groups. Correlation - assesses the strength of association between variables. Regression - computes the values of one variable, given the values of another. ANOVA compares values of a variable across multiple groups. Introducing Communication Research 2e © 2014 SAGE Publications

18. Vocabulary Review ANOVA Bell curve Confidence interval Correlation coefficient Curvilinear relationship Degrees of freedom F value Linear regression MANOVA Multiple regression Nonparametric One-tailed test versus Parametric Part correlation Partial correlation Path analysis r value Regression Sampling distribution Scatterplot Significance Standard error Statistical significance t test t test for dependent samples t test for independent samples Two-tailed test Type I error Type II error Introducing Communication Research 2e © 2014 SAGE Publications

19. Web Resources t- test Calculators http://www.physics.csbsju.edu/stats/t- test_NROW_form.htmlhttp://www.physics.csbsju.edu/stats/t- test_NROW_form.html http://graphpad.com/quickcalcs/ttest1.cfm Introducing Communication Research 2e © 2014 SAGE Publications