data
x | y |
160 | 430 |
180 | 480 |
120 | 330 |
120 | 380 |
70 | 290 |
190 | 520 |
RESULT
SUMMARY OUTPUT | ||||||
Regression Statistics | ||||||
Multiple R | 0.968285642 | |||||
R Square | 0.937577085 | |||||
Adjusted R Square | 0.921971356 | |||||
Standard Error | 24.65447499 | |||||
Observations | 6 | |||||
ANOVA | ||||||
df | SS | MS | F | Significance F | ||
Regression | 1 | 36518.62745 | 36518.62745 | 60.07903226 | 0.001492752 | |
Residual | 4 | 2431.372549 | 607.8431373 | |||
Total | 5 | 38950 | ||||
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | |
Intercept | 140.0980392 | 35.62751033 | 3.932299448 | 0.01706995 | 41.18021254 | 239.0158659 |
x | 1.892156863 | 0.244115678 | 7.751066524 | 0.001492752 | 1.214383082 | 2.569930643 |
y^= 140.098 + 1.892* x
option C) is correct graph
X | Y^ |
170 | 461.7647059 A) |
90 | 310.3921569 A) |
150 | 423.9215686 A) |
210 | not meaningful D) |
Find the equation of the regression line for the given data. Then construet a scatter plot...
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line (Each pair of variables has a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The caloric content and the sodium content (in milligrams) for 6 beef hot dogs are shown in the table below. Calories, x 150 170 130 120 90 180 (a)...
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