A researcher wants to study the performance of high school students of district W in the mathematics final exam. To study the performance, he uses the marks scored by the students in mathematics M as a function of the average number of hours spent by the student on practice H and number of days the student attended the mathematics class in school D. For his study, he selects a random sample of 150 high school students and estimates the following regression function: M= 10.25 + 2.25H +2.75D. The researcher wants to test whether or not changing the average number of hours spent by the student on practice has a statistically significant impact on the marks scored by the students in mathematics. Keeping the other variables constant, the null and the alternative hypotheses of the test conducted by the researcher are Ho B =0 vs. H, B, #0. The test statistic for the test is 2.50 Therefore, the p-value of the test is (Round your answer to two decimal places.) v the null hypothesis. If the study uses two-sided test with the 5% significance level, then the p-value suggests that we The researcher now wants to test whether or not increasing the number of days the student attended the mathematics class in school significantly improves the marks scored by the students in mathematics. Keeping the other variables constant, the researcher wants to calculate the p-value for the test Ho B, =0 vs. H, B >0. The test statistic for this test is 2.55. Enter your answer in each of the answer boxes. UPUCUS
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.
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