The following table shows the selling prices, in thousands of dollars, and the square footages of five randomly selected houses recently sold by a real estate company. The data have a sample correlation coefficient, rounded to three decimal places, of 0.651 Using α0.01and the data given below, test the significance of the population correlation coefficient between a house's selling price and its square footage. What conclusions can you draw?
Selling Price |
$259 |
$194 |
$254 |
$170 |
$250 |
|
---|---|---|---|---|---|---|
Square Footage |
2745 |
1861 |
2193 |
2183 |
2386 |
1) What are the correct null and alternative hypotheses?
2) What is the test statistic? t=
3) What is the p-value? p-value=
4) State the conclusion. _______ H0. There ____ enough evidence from the sample to conclude that p is _______ zero.
The following table shows the selling prices, in thousands of dollars, and the square footages of...
14. 10 pts. Seven randomly selected houses have the following selling prices (in thousands of Philippine pesos) and floor areas (in square ft.) Selling price: 258, 191, 253, 168, 249, 245, 282 . Floor area: 2730, 1860, 2140, 2180, 2310, 2450, 2920 Using the Spearman Rank Correlation Coefficient Test, determine the strength and direction of the relationship between these two variables. Further, test the significance of the coefficient using α 0.05.
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 alphaαequals=0.05 Is there sufficient evidence to conclude that there is a linear correlation between the two variables? Selling price (x): 404, 304, 379, 432, 456, 478, 318, 354, 415, 330, List price (y): 414, 316, 387, 439, 487, 476, 320, 370, 430, 431...
A local realtor wishes to study the relationship between selling price (in $) and house size (in square feet). A sample of 10 homes is selected at random. The data is given below: PRICE HOUSESIZE 100000 1600 107000 1750 121000 1900 124000 2150 132000 2400 140000 2300 144000 2400 158000 2700 170000 3000 182000 2900 a) Find the regression equation relating Price to Square Footage. b) Calculate the correlation coefficient, accurate to three decimal places c) Test the significance of...
Assume for a moment that these 20 houses made up the entire population of houses in San Antonio. Use the Data Analysis Sampling function to choose a random sample of 7 house prices from the population. Put a label called "Sample of 7" over the list you create. 4. 3. Highlight all the data, including both Square Footage and Price, and use the Insert Scatter function to create a Scatter Diagram. Change the title and add a linear trend line...
Please help! 4.53. The following table shows the assessed values and the selling prices of eight houses, constituting a random sample of all the houses sold recently in a metropoli- tan area: Assessed value (thousands) (of dollars) 170.3 202.0 162.5 174.8 157.9 181.6 210.4 188.0 Selling price (thousands) (of dollars) 214.4 269.3 206.2 225.0 199.8 232.1 274.2 243.5 (a) Fit a least squares line that will enable us to predict the selling price of a house in that metropolitan area...
please help thank you! Selling Information For Real Estate Value Price SqFt Brick (1 if brick, if othewise) $241,255 3,392 0 $184,518 2,038 1 $176,488 1,906 0 $240,068 3,329 0 $169,760 1,828 0 $185,335 2,081 0 $172,735 1, 9260 $224,281 3,4250 $172,589 1,676 1 $214,635 2,735 1 $199,666 2,373 1 $208,348 2,662 1 $218,360 2, 8341 $230,160 3, 2540 $164,812 1,431 0 $191,560 1,839 1 $203,255 2, 4561 $173,325 1,530 $168,073 1.381 1 $179,620 1,4571 TABLE 4 Industrial CEO Salary...
1. Selling price in millions of shilling and size of homes Table Price Size Price Size Price Size (‘000) (sq. ft.) (‘000) (sq. ft.) (‘000) (sq. ft.) 268 1897 142 1329 83 1378 131 1157 107 1040 125 1668 112 1024 110 951 60 1248 112 935 187 1628 85 1229 122 1236 94 816 117 1308 128 1248 99 1060 57 892 158 1620 78 800 110 1981 135 1124 56 492 127 1098 146 1248 70 792 119 ...
Solve 4-23 Please 4-22 The following data give the selling price, square footage, number of bedrooms, and age of houses that have sold in a neighborhood in the past 6 months. Develop three regression models to predict the selling price based upon each of the other factors individually. Which of these is best? SELLING PRICE (S) SQUARE FOOTAGE BEDROOMS AGE (YEARS) 84,000 1,670 79,000 1,339 91,500 1,712 120,000 1,840 127.500 2,300 132.500 2,234 145.000 2,311 164.000 2,377 155,000 2,736 168,000...
Excel Problem 2 - Chapter 12: PART B: The following data give the selling price, square footage, and age of houses that have sold in a Bend, OR in the past 6 months (note that this is the same base data as Part A, above, with new variables added). Selling Price ($) Square Footage Age (Years) 84,000 1,670 30 79,000 1,339 25 91,500 1,712 30 120,000 1,840 40 127,500 2,300 18 132,500 2,234 30 145,000 2,311 19 164,000 2,377 7...
One of the biggest factors in determining the value of a home is the square footage. The accompanying data represent the square footage and selling price (in thousands ofdollars) for a random sample of homes for sale in a certain region. Complete all parts below (A.) Which variable is the explanatory variable? a. selling price b. square footage Square Footage, x Selling Price ($000s), y 2221 382.7 3046 353.4 1175 197.2 1938 332.2 3166 630.2 2857 383.9 4086 623.6...