P R 309 Study Guide - Final Guide: Coefficient Of Determination, Dependent And Independent Variables
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correlation:
Ā | medInc $ | HS degree % |
med inc | 1 | Ā |
HS degree % | -0.033158666 | 1 |
regression:
multiple R | .03315867 |
R Square | .0010995 |
adjusted r sq | -.0177477 |
standard error | 6902.6743 |
observation | 55 |
Ā | df | ss | ms | f | sig. f |
regression | 1 | 2779601.33 | 22779601.33 | .05833749 | .81007522 |
residual | 53 | 2525286360 | 47646912.5 | Ā | Ā |
total | 54 | 25280659 | Ā | Ā | Ā |
Ā | coefficients | standard error | t stat | p-value | lower 95% | upper 95% | lower 95.0% | upper 95.0% |
interpret | 42273.3497 | 13809.7807 | 3.0611665 | .00345814 | 14574.4373 | 69972.2621 | 14574.4373 | 69972.2621 |
hs degree | -49.414226 | 204.587042 | -.2415316 | .81007522 | -459.76387 | 360.935414 | -459.76386 | 360.935414 |
a. very briefly interpret the estimated correlation coefficient...the direction and strength of the correlation
b. List and label the dependent variable and independent variable
c. based on regression results if a country's percentage of the population with at least a high school diploma increases by 1 by how much and in one direction does a country's median income change?
d. what is the predicted medinc for an HS degree of 70%
e. what proportion of the variation in medinc is explained by our regression model explained by variation in HS degree?
1. Write the subsequent demand equation, with Qd as the dependent variable; price, advertising, product development, and rel price as the independent variables.
2. How strong is the relationship between quantity demanded and the set of independent variables? List and explain 2 measures of this strength.
3. Which variable is most important in determining quantity demanded? Why?
Regression Statistics | Ā | Ā | Ā | Ā | Ā | Ā | Ā | |
Multiple R | 0.655864641 | Ā | Ā | Ā | Ā | Ā | Ā | Ā |
R Square | 0.430158427 | Ā | Ā | Ā | Ā | Ā | Ā | Ā |
Adjusted R Square | 0.104534671 | Ā | Ā | Ā | Ā | Ā | Ā | Ā |
Standard Error | 102678.3385 | Ā | Ā | Ā | Ā | Ā | Ā | Ā |
Observations | 12 | Ā | Ā | Ā | Ā | Ā | Ā | Ā |
Ā | Ā | Ā | Ā | Ā | Ā | Ā | Ā | Ā |
ANOVA | Ā | Ā | Ā | Ā | Ā | Ā | Ā | Ā |
Ā | df | SS | MS | F | Significance F | Ā | Ā | Ā |
Regression | 4 | 55709596185 | 13927399046 | 1.321029008 | 0.349980066 | Ā | Ā | Ā |
Residual | 7 | 73799888386 | 10542841198 | Ā | Ā | Ā | Ā | Ā |
Total | 11 | 1.29509E+11 | Ā | Ā | Ā | Ā | Ā | Ā |
Ā | Ā | Ā | Ā | Ā | Ā | Ā | Ā | Ā |
Ā | Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% |
Intercept | 1422378.519 | 1185014.572 | 1.200304665 | 0.269060955 | -1379735.677 | 4224492.715 | -1379735.677 | 4224492.715 |
X Variable 1 | -247037.6649 | 160481.181 | -1.539355975 | 0.167610603 | -626515.3574 | 132440.0276 | -626515.3574 | 132440.0276 |
X Variable 2 | 0.081609431 | 1.398101115 | 0.058371623 | 0.955083996 | -3.22437437 | 3.387593232 | -3.22437437 | 3.387593232 |
X Variable 3 | -1.015253706 | 3.150288749 | -0.322273222 | 0.756657161 | -8.46450288 | 6.433995469 | -8.46450288 | 6.433995469 |
X Variable 4 | 177211.9244 | 145755.2053 | 1.215818838 | 0.263460235 | -167444.3689 | 521868.2176 | -167444.3689 | 521868.2176 |