Listed below are annual data for various years. The data are weights (metric tons) of imported lemons and car crash fatality rates per 100,000 population. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value using a = 0.05. Is th sufficient evidence to conclude that there is a linear correlation between lemon imports and crash fatality rates? Do the results suggest imported lemons cause car fatalities? Lemon Imports Crash Fatality Rate 232 265 358 481 534 15.8 15.7 15.5 15.3 14.8 What are the null and alternative hypotheses? О А. Но: р30 О В. Но: р#0 H7:p<0 H1:p=0 OC. Ho: p=0 O D. Ho:p=0 H:p>0 H:p#0 Construct a scatterplot. Choose the correct graph below. OA. В. OC. O D. Ay 17- Ay 17- Ay 17- Ay 17- 16- 16- 16- 16- 15- 15- 15- 15- X 14+ 14- 14+ 14+ 200 400 600 200 400 600 200 400 600 200 400 600 The linear correlation coefficient is r= (Round to three decimal places as needed.) The test statistic is t=. (Round to three decimal places as needed.) The P-value is. (Round to three decimal places as needed.) Because the P-value is v than the significance level 0.05, there sufficient evidence to support the claim that there is a linear correlation between lemon imports and crash fatality rates for a significance level of a = 0.05.
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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