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**Previous **Chap 10 Nonexperimental Research: Descriptive and Causal-Comparative Designs

* ***Chapter 11 Complete**

*p. 319: #1(State advantages an disadvantages of correlational research designs)
*

Advantages and Uses of Correlational Research p324

· Useful for studying problems in education and other social sciences

· Enable researchers to analyze the relationship among a large # of variables

· Identify the cause and effect of educational phenomenon.

· They provide information concerning the degree of the relationship between the variables being studied.

P328 - 329

Weaknesses of Correlation studies

· Shot gun approach to correlation studies: a large # of variables are measured and subjected to correlation analysis even when the researcher has no theoretical basis or even commonsensical rational to justify their inclusion.

· The problem with this type of study is

1. the participants are inconvienced

2. expensive when a large number of measures are used

3. measures are likely to be correlated by chance.

*#3(Draw appropriate inferences from correlation coefficients about the degree, direction, and possible causal nature of relationships between variables)*

P322

The Mathmatics of Correlation

Line of best fit represents the best prediction of a persons score.

· Correlation coefficient is used to express the degree and direction of relationship between two or more variables.

o Perfectly positive relationship the correlation coefficient is 1

o Perfectly negative relationship the correlation coefficient is –1

o No relationship is 0

o If 2 variables are somewhat related, the coefficient will have a value between 0 and 1(positive) or 0 and -1(negative)

*#4(Describe the procedures involved in conducting a study that explores cause-and-effect relationships)*

Planning a Causal Relationship study

Basic Research Design

· The primary purpose of causal relationship studies is to identify the cause and effects of important educational phenomena or events or things.

1. The Problem

a. The first step is to identify specific variables that show promise for being studied.

b. A review of current research often is helpful in identifying the problem or variable to study.

2. Selection of Research Participants

a. Select participants who can be measured on the variable to be studied.

b. It is important to select a homologous group. Otherwise the causal relationship between the variables might be explained by the differences in the group rather than the variable.

3. Data Collection

a. Collection of data for a Causal study can be done by various methods

1. Standardized test

2. Questionnaires

3. Interviews

b. The only requirement is that the data must be in a quantifiable form.

4. Data Analysis

a. Data is analyzed by correlation of the scores on a phenomenon that represents the variable of interest and scores on a variable thought to be related to that phenomenon.

*#5(Describe the procedures involved in conducting a prediction study)*

p329

Planning a Prediction Study

Types of prediction studies

· Prediction studies provide 3 types of information

1. the extent to which a criterion behavior pattern can be predicted

2. data for developing a theory on that criterion

3. evidence about the predictive validity of the test that were correlated with the criterion behavior.

P360

· statistic significance of a correlation coefficient is determined by the size of the sample. The larger the sample the lower the coefficient needs to be to be significant.

· Prediction studies, statistical significance is of little consequence because correlation coefficients usually must exceed the specific alpha level(.05) to be practical.

· Practical significance is more important than statistical significance.

*#14(Interpret the magnitude and statistical significance of correlational coefficients in prediction research and research that explores cause-and-effect relationships)
*

P360

· statistic significance of a correlation coefficient is determined by the size of the sample. The larger the sample the lower the coefficient needs to be to be significant.

· Prediction studies, statistical significance is of little consequence because correlation coefficients usually must exceed the specific alpha level(.05) to be practical.

· Practical significance is more important than statistical significance.

P362

· A phi coefficient of .20 tells us that if a teacher uses the technique, a higher percentage of students will pass the course, but not which student.

· To predict a particular student the coefficient needs to be .7 at least.

· When interoperating the magnitude of correlation coeff. Is that many factors influence the behavior patterns and personal characteristics of primary intrest to educators.

· The influence of any one factor is not likely to be large.

· Correlations in the range of .2 or .4 might be all that is expected to find for many relationships.

· It is better than nothing. If it is a really important thing like death; then its good or practically significant.

Square the coefficient to get the % of variance or how much it is in control or due to the variable being tested. Much like effect size.

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