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Descriptive Statistics Exploratory Data Analysis (EDA) • Searching for patterns in the data Data Organization • • • • Coding sheets/scripts Stacked vs. Unstacked format Data entry problems - transcription errors Grouped vs. Individual Data Graphing and Visualizing Data • Bar graphs - best when the IV is categorical (nominal) • Line graphs - best for illustrating functional relationships between variables Line Graph Terminology • • • • Increasing vs. decreasing Positive vs. negative acceleration Monotonic vs. non-monotonic Floor vs. ceiling values Scatterplots • Best for two DV's when illustrating correlations or linearity Pie Charts • Best for proportions or percentages Tables vs. Graphs • Numerical precision lost in a graph, but relationships in the data are shown more clearly Frequency Distribution of Data • Histogram – Columns should not be too narrow or too wide – Positive vs. negative skew – Normal distributions – Outliers • Stemplot – Stem + leaf – All values are seen Measures of Centers of Distributions • Center – Mode – Median – Mean • Choosing a center: – Skew - median – Normal -mean Measures of Spread of Distributions • Range – Problems: sensitive to outliers; scores in between not taken into account • • • • Interquartile range Variance Standard Deviation Choice of measure of spread: – If there are outliers or skew, choose interquartile The 5-Number Summary • min and max scores • 1st quartile, median, and 3rd quartile scores • Boxplot - visual representation of the 5number summary Statistical Measures of Description • Used to describe data; measures of association between variables Measures of Association • Pearson product-moment correlation coefficient (Pearson R) • Used for two variables with continuous values • Positive and negative relationships denoted • Magnitude of the number tells you the degree of linear relationship between the two variables • Factors that affect magnitude of the Pearson R: – Outliers – Restricted range of scores – Non-normal distribution of scores Other Correlation Tests • Point-biserial correlation – Used when one variable is dichotomous • Spearman rank order correlation (rho) – Used to determine monotonicity • Phi coefficient – Used when both variables are dichotomous Other Analyses • Linear regression analyses – Used for predicting scores and values • Multivariate analyses – Used for analyzing more than one variable at a time