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Lecture Conducting and reading research in health and human performance (4/e): Chapter 13 - Ted A. Baumgartner, Larry D. Hensley

Chapter 13 - Descriptive data analysis. The main contents of the chapter consist of the following: Statistics, 3 basic steps in data analysis, descriptive statistics, types of scores, scales of measurement, computer analysis,. | Chapter 13 Descriptive Data Analysis Statistics Science is empirical in that knowledge is acquired by observation Data collection requires that we make measurements of our observations Measurements then yield data Statistics are used for analyzing data 3 Basic Steps in Data Analysis Select the appropriate statistical technique Apply the technique Interpret the result Descriptive statistics Used to organize, simplify, and summarize the collected data Data typically consist of a set of scores called a distribution. These scores result from the measurements taken The original measurements or values in a distribution are called raw scores Types of Scores Continuous a continuous progression from the smallest possible amount to the largest possible amount, with measurement theoretically possible at any point along the continuum; may be expressed as a fraction (e.g., height, weight, temperature, strength) Discrete measurement and classification are possible only in whole units; no fractional units (e.g., size of family, number of schools in country) Dichotomous – 2 category variable (yes/no; alive/dead) Scales of Measurement Nominal Ordinal Interval Ratio Nominal Merely classifies objects in accordance with similarities and differences with respect to some property; no hierarchy of scores Examples color of hair gender response to a yes/no question shoe preference Ordinal Type of data that is characterized by the ability to rank order on the basis of an underlying continuum No common unit of measurement Examples class ranks place of finish in a race Interval Data having known and equal distances between score units, but having an arbitrary zero point Example temperature on Fahrenheit scale Ratio Possesses same properties of interval data, but does have a true zero point Examples height or weight distance measurement Computer Analysis Variety of computer programs for statistical computations; mainframe and desktop SPSS See Appendix A in textbook for more information SAS | Chapter 13 Descriptive Data Analysis Statistics Science is empirical in that knowledge is acquired by observation Data collection requires that we make measurements of our observations Measurements then yield data Statistics are used for analyzing data 3 Basic Steps in Data Analysis Select the appropriate statistical technique Apply the technique Interpret the result Descriptive statistics Used to organize, simplify, and summarize the collected data Data typically consist of a set of scores called a distribution. These scores result from the measurements taken The original measurements or values in a distribution are called raw scores Types of Scores Continuous a continuous progression from the smallest possible amount to the largest possible amount, with measurement theoretically possible at any point along the continuum; may be expressed as a fraction (e.g., height, weight, temperature, strength) Discrete measurement and classification are possible only in whole units; no .