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Mathematics, 06.08.2021 01:00 melkumathurin

he following data was collected to explore how the number of square feet in a house, the number of bedrooms, and the age of the house affect the selling price of the house. The dependent variable is the selling price of the house, the first independent variable (x1) is the square footage, the second independent variable (x2) is the number of bedrooms, and the third independent variable (x3) is the age of the house. Effects on Selling Price of Houses Square FeetNumber of BedroomsAgeSelling Price 3033515287300 2497513279400 2466411279200 1622410218300 147548190600 144536187600 142932155900 127122109300 119721106600 Step 1 of 2 : Find the p-value for the regression equation that fits the given data. Round your answer to four decimal places.

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On a certain portion of an experiment, a statistical test result yielded a p-value of 0.21. what can you conclude? 2(0.21) = 0.42 < 0.5; the test is not statistically significant. if the null hypothesis is true, one could expect to get a test statistic at least as extreme as that observed 21% of the time, so the test is not statistically significant. 0.21 > 0.05; the test is statistically significant. if the null hypothesis is true, one could expect to get a test statistic at least as extreme as that observed 79% of the time, so the test is not statistically significant. p = 1 - 0.21 = 0.79 > 0.05; the test is statistically significant.
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he following data was collected to explore how the number of square feet in a house, the number of b...
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