sr.no. | height (X) | stories (Y) | X^2 | Y^2 | XY |
1 | 778 | 51 | 605284 | 2601 | 39678 |
2 | 621 | 47 | 385641 | 2209 | 29187 |
3 | 519 | 44 | 269361 | 1936 | 22836 |
4 | 510 | 41 | 260100 | 1681 | 20910 |
5 | 494 | 38 | 244036 | 1444 | 18772 |
6 | 473 | 36 | 223729 | 1296 | 17028 |
total | 3395 | 257 | 1988151 | 11167 | 148411 |
519 Find the equation of the regression line for the given data. Then construct a scatter...
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Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of six notable buildings in a city. Height comma xHeight, x 764 625 520 510 492...
Find the equation of the regression line for the given data. Then construct a scater plot of the data and draw the regression line (The pair of variubles have a significant comelation) Then use the regression equation to predict the vakue of y for each of the given x-values, if meaningul The table below shows the heights (in feet) and the number of shories of six notable buildings in a city 758 Height, K Stories, y 621 47 (a)490 feet...
Find the equation of the regression line for the given data. Then construct a scatter plot of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of Height, Stories, y data and draw the regression line. (The pair of variables have a signiicant correlation.) Then use the regression equation to predict the value of y for each of the sb. notable buildings in a city 775 53 619 47 519 46...
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variaties have a significant correlation) Then use the regression equation to predict the value of yo each of the given x-values, if meaningful. The table below shows the height in feet) and the number of stories of six notable buildings in a city Heights 772 5110 503 483 Stories 51 (a)x= 501 foot...
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of six notable buildings in a city Height, x 768 628 518 511 491 478 (a)...
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significa correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of six notable buildings in a city. Height, x 758 621 518 510 492 483 (a)...
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables has a significant correlation.) Then use the regressiorn equation to predict the value of y for each of the given x-values, if meaningful. The table shows the shoe size and heights (in) for 6 men Shoe size: x-T8.5 110T15|130|135 (a) x=size 10 0 (b)x-size 10.5 3.5 745 725(c)x-s size 16.0 (d)x- size...
Find the equation of the regression line for the given data Then construct a cate plot of the data and draw the regressionline(The pair of variables have a significant correlation) Then use the regression equation to pred the value of y for each of the given x-values, if meaningful The table below shows the heights in feet) and the number of stories of she notable buildings in a city Height, 766 620 508 (a)x562 fost (h) x646 feet Stories, y...
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The number of hours 6 students spent for a test and their scores on that test are shown below. Hours spent studying, X 2 5 5 (a) x =...