10.2.22 Question Help The data show the bug chirps per minute at different temperatures. Find the regression equation, letting the first variable be the independent (x) variable. Find the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute. Use a significance level of 0.05. What is wrong with this predicted value? Chirps in 1 min Temperature (°F) 847 765 990 1018 813 928 73.5 68.6 82.4 81.5 75 78.8 What is the regression equation? ŷ-D•Ox %3D (Round the x-coefficient to four decimal places as needed. Round the constant to two decimal places as needed.)

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Find the regression​ equation, letting overhead width be the predictor​ (x) variable. Find the best predicted weight of a seal if the overhead width measured from a photograph is 2.5 cm. Can the prediction be​ correct? What is wrong with predicting the weight in this​ case? Use a significance level of 0.05.   Overhead Width​ (cm) 7.6 7.4 9.8 8.8 9.3 7.3   Weight​ (kg) 142 163 256 188 231 156       The regression equation is y= + x. ​(Round to one decimal place as​ needed.)   The best predicted weight for an overhead width of 2.5 cm is kg? ​(Round to one decimal place as​ needed.)   Can the prediction be​ correct? What is wrong with predicting the weight in this​ case?     A. The prediction cannot be correct because a negative weight does not make sense. The width in this case is beyond the scope of the available sample data.   B. The prediction cannot be correct because a negative weight does not make sense and because there is…

Write the linear model to test the hypothesis that there is no treatment effect. Clearly describe each term in the model, and the range of the subscripts. Write the null hypothesis that you are testing.   Call: lm(formula = score ~ list, data = hearing)   Residuals:      Min       1Q   Median       3Q      Max -14.7500  -5.5833  -0.2083   6.3333  16.4167   Coefficients:             Estimate Std. Error t value Pr(>|t|)    (Intercept)   32.750      1.612  20.315  < 2e-16 *** listList2     -3.083      2.280  -1.352  0.17955    listList3     -7.500      2.280  -3.290  0.00142 ** listList4     -7.167      2.280  -3.144  0.00225 ** --- Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1   Residual standard error: 7.898 on 92 degrees of freedom Multiple R-squared:  0.1382,  Adjusted R-squared:  0.1101 F-statistic: 4.919 on 3 and 92 DF,  p-value: 0.00325

The data show the bug chirps per minute at different temperatures. Find the regression​ equation, letting the first variable be the independent​ (x) variable. Find the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute. Use a significance level of 0.05. What is wrong with this predicted​ value? Chirps in 1 min  1118  796  1161  918  1103  1219 Temperature (F)   82    72.2   92.2   73   87.5   94.4

Using the data in the Excel spreadsheet "auto.xlsx", estimate a regression to answer the following question. How much does a 1 inch increase in LENGTH corresponds to a _________________ dollars increase in PRICE. Use negative values if it results in a decreased price. Round your answers to two decimals.