## Midterm Review Sheet

 Text Concepts Text Concepts (continued) Parameter versus Statistic Properties of the t distribution Population versus Sample degrees of freedom Descriptive versus Inferential Statistic Quantitative versus Qualitative data sample as interval versus nominal levels of measurement Pearson product moment correlation - properties of the measure and when to use it (level of measurement) Testing r for significance Other measures of r (Spearman, Point biserial, Phi) Levels of Measurement Discrete versus Continuous variables Regression Scatterplots Equation y' = bx + a Interpretation of slope and intercept Properties of predicted and residual values (y' and y-y') Variance partitioning, r2, and proportional reduction in error Regression towards the mean Standard error of estimate Z transformations Sampling Error Frequency Distribution Relative frequency Cumulative Frequency Histograms Box plots - know what info they convey Stem and Leaf plot - why use? Measures of Central Tendency Mean, Median Mode Relationship to levels of measurement Effect of Outliers on these Effects of shape of distribution Measures of Variability Sum of Squares, Variance, St. deviation, Range Interquartile range Relationship to levels of measurement Effect of outliers on these Effects of shape of distribution properties of the St. deviation interpreting the magnitude of St. deviation Part and partial correlation zero-order correlation variance partitioning predicted and residual variance interpreting Venn diagrams distinguishing between part and partial correlations which should be larger and why? Normal Distribution Properties of the normal Percentile rank Areas under the curve Probabilities Multiple Regression Part 1 basic mathematical model multiple slopes and single intercept interpreting R and R2 prediction scores and residuals significance testing (F test) assumptions of Multiple Regression looking violations - normality, linearity, multicolinearity Entry strategies (forward stepwise and forced entry) ways to assess independent contributions (b, beta, r, part and partial r) Change in r2 Basic Research Design IV and DV Levels of Measurement Between versus within group designs correlational versus experimental designs Statistical Estimation Point estimates Confidence intervals Relationship between point and interval estimators Properties of estimators (bias, consistency, efficiency) Logic of hypothesis testing Ho and Ha Conditional probability Sampling distribution under Ho Test statistic (index of departure from Ho) p value and alpha level Type I and Type II errors Factors that affect Type I and Type II errors Statistical power and the factors that affect it One versus two tailed tests Sampling Distribution Constructing a sampling distribution Standard error of the Mean Standard error of sampling proportion Central limit theorem Use in Statistical Inference Effect of sample size on sampling distribution Tests covered to date (know assumptions and when to use each test) One sample z test for the mean One sample t-test for the mean Two sample t-test between groups (pooled estimate) Two sample t-test between groups (separate variance estimate) Two sample t-test within groups One sample sample correlation test