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Lecture

# Chapter 5 - research methods.docx

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School
Department
Kinesiology & Health Science
Course
KINE 2049
Professor
Merv Mosher
Semester
Fall

Description
KINE2049 Research methods Chapter 5: Experimental research 1. Explain the difference between the terms parameter and statistic a. Parameters are the facts gathered about the whole population (μ) b. Statistics are gathered from sample groups (parts of populations) and are regarded as estimates of parameters (x) 2. Discuss the qualities of proper sampling a. Clearly identify the population of interest, describing who is and is not included in the experiment b. Identify the sample group to avoid any misrepresentation of population (biased) c. Determine the sample size. Generally, large samples increase the accuracy. However one must consider the cost, and whether the large sample truly represents the population. (Literary digest article on presidential survey; large sample however it only reflected 1 class of people thus it was biased) d. Randomly select sample where each member has equal chance of selection, and selection of one does not hinder the probability of others 3. Describe the differences between a random sample, a stratified sample, and a cluster sample a. Random sample (simple) – the selection of sample is random and selection of one does not alter the selection of another b. Random sample (stratified) – the selection is random, but the final sample would realistically represent ratios of real populations. Utilized when the ratio is relevant to study. c. Cluster sample – selecting samples with unknown characteristics, and when selecting whole samples are impossible. 4. Explain the difference between an independent variable, a dependent variable, and a control variable a. Independent variable – variables manipulated by the investigator to show possible cause and effect b. Dependent variable – the variable or outcome measured. c. Control variable – the variable(s) that must remain constant in order to isolate the dependent variable 5. Describe why independent variables have levels Having many levels will allow any independent/dependent correlation to be shown. 6. Explain how operational definitions define variables a. How the variable (i.e bodyweight) is defined in the research will determine whether it is independent (weight class of subjects) or dependent (weight gained/loosed by subjects) 7. Understand the threat imposed by confounding variables on research findings Confounding variables can occur without the knowledge or researchers, and may happen so discreetly. A valid report must control any possible confounding variables or at least attempt to identify any variables, failing to do so results in criticism of method. KINE2049 Research methods 8. Differentiate between primary variance, secondary variance, and error variance a. Primary variance (systematic) – the wanted and consistent variation due in part to the independent variable. Maximum primary variance can be achieved by having independent variables change greatly but linearly so correlation can be seen. b. Secondary variance (extraneous) – the unwanted and consistent variation in the measurement. Can be controlled with careful selection of subjects, using blind experimentation, and correctly calibrated instruments. c. Error variance – unwanted and inconsistent measurement due to uncontrollable variations or
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