5. Test for a linear correlation between price and bedrooms in South Salinas 6. Test for a linear correlation between price and bedrooms in North Salinas. 7. Test the claim that average house prices are the same in South and North Salinas. South Salinas: Price Square Feet 599 1512 465 1023 595 2436 1185 3559 640 2093 566 1531 499 1132 611 1577 439 1536 512 1630 999 2845 755 2661 405 895 650 1951 489 971 652 2043 629 1848 420 766 639 2130 482 1400 605 2600 455 1556 615 2105 690 2003 North Salinas: Price Square Feet 585 2473 402 1118 379 932 485 1240 476 1387 321 720 532 1569 555 1928 395 1205 375 948 599 1861 695 2591 522 1443 492 1215 425 1034 562 1215 509 1102 549 1877 515 1308 544 1701 545 1427 570 2602 599 1823 409 936 Bedrooms 3 2 4 5 4 3 3 3 3 3 4 4 2 3 Bedrooms 4 2 2 3 3 2 3 3 2 2 3 4 3 3 2 3 3 4 4 3 2 4 3 5 3 4 3 3 5 4 2
Added by Edward B.
Close
Step 1
To calculate the correlation coefficient, we can use the formula: r = (nΣxy - ΣxΣy) / sqrt((nΣx^2 - (Σx)^2)(nΣy^2 - (Σy)^2)) where n is the number of data points, Σxy is the sum of the products of x and y, Σx is the sum of x values, Σy is the sum of y values, Show more…
Show all steps
Your feedback will help us improve your experience
Shubham Sharma and 74 other Intro Stats / AP Statistics educators are ready to help you.
Ask a new question
Labs
Want to see this concept in action?
Explore this concept interactively to see how it behaves as you change inputs.
Key Concepts
Recommended Videos
Oluwadamilola A.
For the paired data, do a complete regression analysis: a) Draw a scatter plot graph for the data b) Compute the value of the correlation coefficient. c) Use the Critical Value (CV) from the table to determine if there is a significant linear correlation. d) Determine the linear regression equation and plot the line on the scatter plot. e) Find the best predicted value. Below are the size and asking price of ten recently listed homes in Big Bear City. What is the best predicted asking price for a home with square footage of X = 1020? Size (sq. ft.) X 1284 940 3408 780 1616 924 1593 650 1056 1783 Asking Price Y 215 190 525 175 342 249 319 119 249 298
James K.
The table below reflect the price of a house based on the size in square feet, number of bedrooms, number of bathrooms, and the location (translated into the wealth factor). Based on this data, using linear regression, estimate the prices for the following houses. (a) A house with 2900 Sq. feet area, 2 bathrooms, 2 bedrooms, and the wealth factor of 3. (b) A house with 1850 Sq. feet area, 3 bathrooms, 3 bedrooms, and the wealth factor of 9.
Rachel G.
Recommended Textbooks
Elementary Statistics a Step by Step Approach
The Practice of Statistics for AP
Introductory Statistics
Watch the video solution with this free unlock.
EMAIL
PASSWORD