The authors of a paper presented a correlation analysis to investigate the relationship between maximal lactate level x and muscular endurance y. The accompanying data was read from a plot in the paper. 390 740 760 790 860 1,035 1,210 1,240 1,290 1,390 1,465 1,490 1,515 2,190 y 3.70 4.10 5.00 5.10 3.90 3.60 6.40 6.98 7.45 4.85 7.90 4.35 6.50 8.80 Sy = 2,638,258.929, S = 37.7881, S = 7,398.846. A scatter plot shows a linear pattern. (a) Test to see whether there is a positive correlation between maximal lactate level and muscular endurance in the population from which this data was selected. (Use a = 0.05.) State the appropriate null and alternative hypotheses. O Ho: p = 0 Hip >0 O Ho: p =0 H:p = 0 O Ho: p = 0 H:p = 0 O Ho: p = 0 H:p< 0 Compute the value of the sample correlation coefficient, r. (Round your answer to four decimal places.) %3D Calculate the test statistic and determine the P-value. (Round your test statistic to one decimal place and your P-value to three decimal places.) p-value =
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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