The data below shows the selling price (in hundred thousands) and the list price (in hundred thousands) of homes sold. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value using α=0.05. Is there sufficient evidence to conclude that there is a linear correlation between the two variables? Selling Price (x) 400 303 376 431 458 476 317 353 417 331 List Price (y) 415 315 389 436 488 476 322 365 434 342 What are the null and alternative hypotheses? A. H0: ρ=0 H1: ρ>0 B. H0: ρ≠0 H1: ρ=0 C. H0: ρ=0 H1: ρ<0 D. H0: ρ=0 H1: ρ≠0 Construct a scatterplot. Choose the correct graph below. A. 300400500300400500xy A scatterplot has a horizontal x-scale from 300 to 500 in intervals of 20 and a vertical y-scale from 300 to 500 in intervals of 20. Ten points are plotted with approximate coordinates as follows: (305, 330); (315, 370); (355, 415); (365, 350); (410, 450); (415, 380); (420, 425); (465, 485); (470, 405); (470, 455). B. 300400500300400500xy A scatterplot has a horizontal x-scale from 300 to 500 in intervals of 20 and a vertical y-scale from 300 to 500 in intervals of 20. Eleven points are plotted with approximate coordinates as follows: (305, 485); (330, 340); (350, 465); (360, 405); (390, 400); (400, 475); (410, 375); (415, 435); (430, 355); (430, 400); (455, 460). C. 300400500300400500xy A scatterplot has a horizontal x-scale from 300 to 500 in intervals of 20 and a vertical y-scale from 300 to 500 in intervals of 20. Eleven points are plotted with approximate coordinates as follows: (305, 485); (335, 460); (355, 365); (360, 450); (380, 425); (390, 400); (410, 375); (415, 435); (420, 390); (430, 355); (460, 345). D. 300400500300400500xy A scatterplot has a horizontal x-scale from 300 to 500 in intervals of 20 and a vertical y-scale from 300 to 500 in intervals of 20. Ten points are plotted with approximate coordinates as follows: (305, 315); (315, 320); (330, 340); (355, 365); (375, 390); (400, 415); (415, 435); (430, 435); (460, 490); (475, 475). The linear correlation coefficient r is nothing. (Round to three decimal places as needed.) The test statistic t is nothing. (Round to three decimal places as needed.) The P-value is nothing. (Round to three decimal places as needed.) Because the P-value is ▼ less greater than the significance level 0.05, there ▼ is is not sufficient evidence to support the claim that there is a linear correlation between selling price (in hundred thousands) and the list price (in hundred thousands) of homes sold for a significance level of α=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.
Selling Price (x)
|
400
|
303
|
376
|
431
|
458
|
476
|
317
|
353
|
417
|
331
|
|
---|---|---|---|---|---|---|---|---|---|---|---|
List Price (y)
|
415
|
315
|
389
|
436
|
488
|
476
|
322
|
365
|
434
|
342
|
|
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