Midterm Review Sheet

Text Concepts	Text Concepts (continued)
Parameter versus Statistic	Properties of the t distribution degrees of freedom
Population versus Sample	3 Questions of statistics Is there a relationship? Magnitude of the relationship (effect size) Nature (shape) of the relationship
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 Nominal,Ordinal,Interval,Ratio and binary or nominal / dichotomous 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 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 basic mathematical model multiple slopes and single intercept interpreting R and R2 prediction scores and residuals significance testing (F test) ways to assess independent contributions (beta, standardized beta, part and partial r) assumptions of Multiple Regression looking for violations - normality, linearity, multicolinearity Hierarchical regression Testing for 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 Effect Size measures: Cohen's d and r 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 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 Testing R for significance Testing for change in R2 Two sample t-test between groups (pooled estimate) Two sample t-test between groups (separate variance estimate) Two sample t-test within groups