1. chapter 6 Becoming Acquainted With Statistical Concepts

2. Chapter Outline Why we need statistics Use of computers in statistical analysis Description and inference are not statistical techniques Ways to select a sample Justifying post hoc explanations Difficulty of random sampling and assignment: how good does it have to be? Measures of central tendency and variability Basic concepts of statistical techniques

3. Why We Need Statistics Statistics is an objective way of interpreting a collection of observations. Types of statistics –Descriptive techniques –Correlational techniques –Differences among groups

4. Example of Correlation

5. How Computers Are Used in Statistics Frequently used in offices, labs, and homes for statistical analysis Hardware and software Types of software for statistics –Statistical Analysis system (SAS) –Statistical Package for the Social Sciences (SPSS)

6. Ways to Select a Sample Random sampling: tables of random numbers Stratified random sampling Systematic sampling Random assignment Justifying post hoc explanations How good does the sample have to be? Good enough for our purposes!

7. Measures of Central Tendency and Variability Central tendency scores –Mean: average –Median: midpoint –Mode: most frequent Variability scores –Standard deviation –Range of scores

8. Categories of Statistical Tests Parametric –Normal distribution –Equal variances –Independent observations Nonparametric (distribution free) –Distribution is not normal Normal curve –Skewness –Kurtosis

9. Normal Curve

10. Skewness

11. Kurtosis

12. Statistics What statistical techniques tell us –Reliability (significance) of effect –Strength of the relationship (meaningfulness) Types of statistical techniques –Relationships among variability –Differences among groups Cause and effect: Correlation is no proof of causation.