a researcher’s action research, she seeks to investigate whether a particular intervention works for teaching a mathematical concept. She organizes a diagnostic test (pre-test), taught with her intervention and then did a post-test. The recorded scores for ten students is in the table below: Student ID 01 02 03 04 05 06 07 08 09 10 Pre-test. 66 49 63 70 71 65 75 88 87 51 Post-test 69 50 61 72 78 66 75 89 86 54 (i) Draw a scatterplot for the observed scores and superimposed in it a least square regression line. (ii) Compute the Pearson Product Moment Correlation for the two tests and interpret your results.
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
3. In a researcher’s action research, she seeks to investigate whether a particular intervention works for
teaching a mathematical concept. She organizes a diagnostic test (pre-test), taught with her intervention
and then did a post-test. The recorded scores for ten students is in the table below:
Student ID 01 02 03 04 05 06 07 08 09 10
Pre-test. 66 49 63 70 71 65 75 88 87 51
Post-test 69 50 61 72 78 66 75 89 86 54
(i) Draw a scatterplot for the observed scores and superimposed in it a least square regression line.
(ii) Compute the Pearson Product Moment
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