Kine 2049 Chapter 6-9 notes

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

Description
Chapter 6: Experimental Designs What is an experiment? In the experiment in the book for the effect of bicycling on weight loss, the experiment lacks a second level Dependant variable: body weight, independent variable: exercise program = , one-group pre-test-post-test design where a single subject is given a pre-test, treatment, then a post-test Problem with this experiment are that there is not a second level of the independent variable. For a better assessment the program needs a second level which could be: a control group that does not cycle, or a group that rides 15 miles a day rather than 10 miles a day. Basically, the original design lacks a condition against which you can compare the results of the bicycling program Must also identify the control variables such as diet, etc. because otherwise the results may not be because of bicycling alone One group design: Bicycling This is the original study. It has Program Weight 1 independent variable, 1 level, and 1 dependent variable. Two group design: Control Better; it is a 2 level design, Group Weight subjects can be randomly assigned to a group and differences can be because of the bicycling program. Bicycling Program Weight Advantages of Experiments Better than just simple observation, more accurate Experimental control: extraneous variation that may affect the results are controlled/ eliminated My identifying many control variables and changing them up in an experiment, the causal factors can be determined (manipulation of independent variables, measurement of dependant variables, and control of other variables) More than One Independent Variable Advantages: It is more efficient to conduct one experiment with 2-3 independent variables than to conduct many experiments with each single independent variables (saves time, money, # of subjects) Experiments with many variables also reflect the real world better and dont apply just in the lab Ex. Heart rate is affects by duration of exercise, intensity, and age. Thus, you must measure all to get an accurate result Most important reason why multiple independent variables are used is to see how independent variables interact together and affect the dependant variable Disadvantages: as number of independent variables increases, so does the complexity of the experiment and the interpretation of the results Complex= 2-3 independent variables, very complex= 4-5 More than One Dependant Variable Researchers will also measure more than one dependant variable In bike experiment other dependant variables that can be measures are HR, lactic acid levels, etc. Advantages: represents more real life, efficient use of time, subjects, resources Disadvantages: increases complexity, more demand placed on subjects, more interpretation Experimental Design Provide the detail and explanation of the different methods used by researchers to answer question 4 main things it focuses on: 1. Devising subject selection and assignment 2. Writing operational definitions for the independent and dependant variables 3. Selecting appropriate statistical analysis tests 4. Planning the experimental procedures used to gather the data Subject Selection and Assignment 3 basic experimental designs: 1. Independent groups design: an experimental design in which each treatment condition is given to a separate group of subjects. Used when it is important to exclude subject from the second treatment condition. Example: 2 groups; one given aspirin other given placebo, thus no one could take both. Disadvantage: potential for groups to not be equivalent at beginning of the study (ex. In aspirin study one must assume that people in both groups have equal chance of hear attack, etc.) 2. Repeated measures design: the same subjects serve in each condition. It is an experimental design in which 2 or more treatment conditions are administered to the same group of subjects. Choosing this design over the independent groups design depends on the nature of the experiment and the demands placed on the subjects. Advantage: fewer subjects are needed than with independent groups. It is also more sensitive than independent groups design to dependent variable differences. Because the same subjects are in all the treatment conditions, they are identical in every other aspect. Reduces variablilty between subjects and improves the chances of detecting any effects caused by the independent variable a.k.a statistical power Disadvantages: chance of carry-over effects from one treatment to another. Carry over effects are present when exposure to previous treatment affects results for the next treatment. 3. Mixed groups design: combines independent group and repeated measures methods Simple Random Assignment Most common method of assigning subjects to independent variables Examples: drawing names out of a hat, computer system, etc. Matched Random Assignment Has the same goal as simple random assignment, but uses more methods Used when the researcher wants to make sure that both groups are equal on the dependant variable Steps: 1. Select variable that is related to the dependent variable 2. Subjects are then measured on the matching variable 3. Subject with highest scores are paired together and then the 2 groups are divided Matched random assignment ensures that groups are equivalent on some variable prior to the experiment. It doesnt however, make sure that the groups are equivalent on any other variable Carry-Over Effects 1. Order Effects: occurs when the result of treatment 1 is still present when the 2 treatment is given. 2 categories of order effects: a) Practice effects: results in improved performance on the second of 2 measures because the subject learned how to take the test b) Fatigue effects: opposite of practice effects, and happens when performance gets worse on the next tests because of repeated measurements (sources include: physical fatugue, boredom, loss of interest) Counterbalancing Counterbalancing: controlling for order effects in a repeated measures design. Counterbalancing the order in which treatments are presented. It neutralizes the potential order effects in a repeated measures design by exposing the subject to different order of testing conditions either systematically or randomly. (pg 106) With complete counterbalancing, ,all possible orders of presentation are included in the design of the study. It does become more complex when the number of treatment conditions goes beyond 3-4. Latin Squares (pg 107)
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