The following data represents the rate of return of the stock exchange (x) and the rate of return of a certain stock (y). The equation of the least squares regression line is y =0.9764x +0.5975 and the standard error of the estimate is 2.3518. Answer parts (a)(d). 0.23 0.94 1.21 -0.57 -0.59 5.89 1.40 3.86 3.25 -2.53 1.89 -1.91 -2.01 3.00 0.90 O 5.90 -2.58 0.06 1.78 0.06 5.79 -1.57 (a) What is the mean rate of return for the stock if the rate of return of the S&P 500 is 4.24%? y=% (Round to one decimal place as needed.) (b) Construct a 90% confidence interval about the mean rate of raturm of y if x-4.24%. Lower Bound Upper Bound 1% (Round to one decimal place as needed.) (c) Predict the rate of return of the stock if the rate of return on the S&P 500 for a randomly selected month is 4.24%. y-D% (Round to one decimal place as needed.) (d) Construct a 90% prediction interval about the rate of return of y if x 4.24% Lower Bound Upper Bound peeded
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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