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