### Regression Analysis of Heart Weight and Body Weight in CatsThe regression output from a model for predicting the heart weight (in grams) of cats from their body weight (in kilograms) is provided below. The coefficients are estimated using a dataset of 144 domestic cats.#### Regression Output Table:| | Estimate | Std. Error | t value | Pr(>|t|) ||-----------------------|----------|------------|---------|----------|| (Intercept) | -0.357 | 0.692 | -0.515 | 0.607 || body wt | 4.034 | 0.250 | 16.119 | 0.000 || | | | | || *s* | | | | 1.452 || R² | | | | 64.66% || R²adj | | | | 64.41% |The symbols and terms used in the table include:- **Estimate**: The estimated coefficient for each predictor.- **Std. Error**: The standard error of the estimated coefficient.- **t value**: The t-statistic value used to test the null hypothesis.- **Pr(>|t|)**: The p-value associated with the t-statistic.- *s*: The standard error of the regression (residual standard deviation).- R²: The coefficient of determination.- R²adj: The adjusted coefficient of determination.#### Hypothesis Testing:##### (a) Determining HypothesesWhat are the hypotheses for evaluating whether body weight is positively associated with heart weight in cats?- **Null Hypothesis \(H_0\)**: \(\beta_1 = 0\)- **Alternative Hypothesis \(H_A\)**: \(\beta_1 > 0\)The chosen hypotheses are correct based on the detailed setup:\( \circ \) \( H_0: \beta_1 = 0 \) (checked)\( \circ \) \( H_A: \beta_1 > 0 \)#### (b) Conclusion of Hypothesis Test:State the conclusion of the hypothesis test from part (a) in the context of the data. (Use a significance level of 0

(a) The null and alternative hypothesis is, The level of significance is, The sample size is, n =…

The regression output from a model for predicting the heart weight (in g) of cats from their body weight (in kg) is provided below. The coefficients are estimated using a dataset of 144 domestic cats. Estimate Std. Error t value Pr(>|t|) (Intercept) -0.357 0.692 -0.515 0,607 body wt 4.034 0.250 16.119 0.000 S = 1.452 R2 = 64.66% R2 adj = 64.41% (a) What are the hypotheses for evaluating whether body weight is positively associated with heart weight in cats? O Hoi B120 HA: B1 < 0 O Ho: B1 = 0 HA: B1 > 0 O Ho: B1 # 0 HAi B1 = 0 O Hoi B1 = 0 HA: B1 * 0 O Hoi B1 = 0 HA: B1 < 0 (b) State the conclusion of the hypothesis test from part (a) in context of the data. (Use a significance level of 0.05. Enter your test statistic to three decimal places.) The test statistic is T = 0 x with degrees of freedom df = .05 X . The p-value is less than 0.05. Therefore, we reject vv Ho. The data provide strong evidence that body weight is positively associated with heart weight in cats.

The regression output from a model for predicting the heart weight (in g) of cats from their body weight (in kg) is provided below. The coefficients are estimated using a dataset of 144 domestic cats. Estimate Std. Error t value Pr(>|t|) (Intercept) -0.357 0.692 -0.515 0,607 body wt 4.034 0.250 16.119 0.000 S = 1.452 R2 = 64.66% R2 adj = 64.41% (a) What are the hypotheses for evaluating whether body weight is positively associated with heart weight in cats? O Hoi B120 HA: B1 < 0 O Ho: B1 = 0 HA: B1 > 0 O Ho: B1 # 0 HAi B1 = 0 O Hoi B1 = 0 HA: B1 * 0 O Hoi B1 = 0 HA: B1 < 0 (b) State the conclusion of the hypothesis test from part (a) in context of the data. (Use a significance level of 0.05. Enter your test statistic to three decimal places.) The test statistic is T = 0 x with degrees of freedom df = .05 X . The p-value is less than 0.05. Therefore, we reject vv Ho. The data provide strong evidence that body weight is positively associated with heart weight in cats.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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