Consider the accompanying data on x = research and development expenditure (thousands of dollars) and y = growth rate (% per year) for eight different industries. Calculate the test statistic and P-value for this test. (Use a table or technology. Round your test statistic to one decimal place and your P-value to three decimal places.) t= P-value= Use a 90% confidence interval to estimate the average change in growth rate (in % per year) associated with a $1,000 increase in expenditure. (_____,_____)% per yr. x 2,027 5,043 900 3,571 1,157 327 378 191 y 1.90 3.96 2.44 0.88 0.37 −0.90 0.49 1.01
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.
15.2 #2
| x | 2,027 | 5,043 | 900 | 3,571 | 1,157 | 327 | 378 | 191 |
|---|---|---|---|---|---|---|---|---|
| y | 1.90 | 3.96 | 2.44 | 0.88 | 0.37 |
−0.90
|
0.49 | 1.01 |
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