Applied statistics I.

1. Evaluating Numeric Information<br /> Introduction<br /> Guidelines for Numeracy<br /> Source Credibility<br /> Message Content<br /> Evaluating Generalizability<br /> Making Causal Claims<br /> Quality Control Mechanisms in Science<br /> Biases of Information Consumers<br /> Ethical Issues in Data Collection and Analysis<br /> Lying with Graphs and Statistics<br /> Degrees of Belief<br /> Summary<br />2. Basic Research Concepts<br /> Introduction<br /> Types of Variables<br /> Independent and Dependent Variables<br /> Typical Research Questions<br /> Conditions for Causal Inference<br /> Experimental Research Design<br /> Non-experimental Research Design<br /> Quasi- Experimental Designs<br /> Other Issues in Design and Analysis<br /> Choice of Statistical Analysis (Preview)<br /> Populations and Samples: Ideal Versus Actual Situations<br /> Common Problems in Interpretation of Results<br /> Appendix 2 A: More About Levels of Measurement<br /> Appendix 2 B: Justification for Use of Likert and Other Rating Scales as Quantitative Variables (In Some Situations)<br />3. Frequency Distribution Tables<br /> Introduction<br /> Use of Frequency Tables for Data Screening<br /> Frequency Tables for Categorical Variables<br /> Elements of Frequency Tables<br /> Using SPSS to Obtain a Frequency Table<br /> Mode, Impossible Score Values, and Missing Values<br /> Reporting Data Screening for Categorical Variables<br /> Frequency Tables for Quantitative Variables<br /> Frequency Tables for Categorical Versus Quantitative Variables<br /> Reporting Data Screening for Quantitative Variables<br /> What We Hope to See in Frequency Tables for Categorical Variables<br /> What We Hope to See in Frequency Tables for Quantitative Variables<br /> Summary<br /> Appendix 3 A: Getting Started in IBM SPSS ® version 25<br /> Appendix 3 B: Missing Values in Frequency Tables<br /> Appendix 3 C: Dividing Scores into Groups or Bins<br />4. Descriptive Statistics<br /> Introduction<br /> Questions about Quantitative Variables<br /> Notation<br /> Sample Median<br /> Sample Mean (M)<br /> An Important Characteristic of M: Sum of Deviations from M = 0<br /> Disadvantage of M: It is Not Robust Against Influence of Extreme Scores<br /> Behavior of Mean, Median and Mode in Common Real-World Situations<br /> Choosing Among Mean, Median, and Mode<br /> Using SPSS to Obtain Descriptive Statistics for a Quantitative Variable<br /> Minimum, Maximum, and Range: Variation among Scores<br /> The Sample Variance s2<br /> Sample Standard Deviation (s or SD)<br /> How a Standard Deviation Describes Variation Among Scores in a Frequency Table<br /> Why Is There Variance?<br /> Reports of Descriptive Statistics in Journal Articles<br /> Additional Issues in Reporting Descriptive Statistics<br /> Summary<br /> Appendix 4 A Order of Arithmetic Operations<br /> Appendix 4 B Rounding<br />5. Graphs: Bar Charts, Histograms, and Box Plots<br /> Introduction<br /> Pie Charts for Categorical Variables<br /> Bar Charts for Frequencies of Categorical Variables<br /> Good Practice for Construction of Bar Charts<br /> Deceptive Bar Graphs<br /> Histograms for Quantitative Variables<br /> Obtaining a Histogram Using SPSS<br /> Describing and Sketching Bell-Shaped Distributions<br /> Good Practices in Setting up Histograms<br /> Box Plot (Box and Whiskers Plot)<br /> Telling Stories About Distributions<br /> Uses of Graphs in Actual Research<br /> Data Screening: Separate Bar Charts or Histograms for Groups<br /> Use of Bar Charts to Represent Group Means<br /> Other Examples<br /> Summary<br />6. The Normal Distribution and z Scores<br /> Introduction<br /> Locations of Individual Scores in Normal Distributions<br /> Standardized or "z" Scores<br /> Converting z Scores Back into Original Units of X<br /> Understanding Values of z<br /> Qualitative Description of Normal Distribution Shape<br /> More Precise Description of Normal Distribution Shape<br /> Reading Tables of Areas for the Standard Normal Distribution<br /> Dividing the Normal Distribution Into Three Regions: Lower Tail, Middle, Upper Tail<br /> Outliers Relative to a Normal Distribution<br /> Summary of First Part of Chapter<br /> Why We Assess Distribution Shape<br /> Departure from Normality: Skewness<br /> Another Departure from Normality: Kurtosis<br /> Overall Normality<br /> Practical Recommendations<br /> Reporting Information About Distribution Shape, Missing Values, Outliers, and Descriptive Statistics for Quantitative Variables<br /> Summary<br /> Appendix 6 A: The Mathematics of the Normal Distribution<br /> Appendix 6 B: How to Select and Remove Outliers in SPSS<br /> Appendix 6 C: Quantitative Assessments of Departure from Normality<br /> Appendix 6 D: Why Are Some Real-World Variables Approximately Normally Distributed?<br />7. Sampling Error and Confidence Intervals<br /> Descriptive Versus Inferential Uses of Statistics<br /> Notations for Samples Versus Populations<br /> Sampling Error and t