Summary Output |
ANOVA |
|||||
df |
SS |
MS |
F |
Significance F |
|
Regression |
1 |
2.7500 |
-d- |
-e- |
0.632 |
Residual |
-a- |
-b- |
11.45 |
||
Total |
14 |
-c- |
"As per the HOMEWORKLIB RULES, we need to answer for the first question only in multiple posting. Please ask single question in single post."
1) What does the error term in the simple linea regression model
account for?
The error term refers to the sum of deviations within the
regression line.It explains the difference between the theoretical
value of the model and the actual observed result.
Suppose we have a multiple linear regression function of the form Y=+Xi+i
where and are constant parameters
Xi is independent variables and
i is error term
2)What are the parameters of the simple linear model?
The parameter is the intercept and represents the expected response when Xi=0.
The parameter is the slope and represents the expected increment in the response per unit change in Xi.
3) When all the points fall on the regression line, what is the value of the correlation coefficient?
When all the points fall on the regression line,the value of the correlation coefficient would be equal to 1.
There are two situation with value of r.
When r=-1,the graph is as follows.It shows a negative trend.
When r=+1,the graph is as follows.It shows a positive trend.
What does the error term in the simple linear regression model account for? What are the...
Part of an Excel output relating 15 observations of X (independent variable) and Y (dependent variable) is shown below. Provide the values for a-e shown in the table below. (See section 15.5) Summary Output ANOVA df SS MS F Significance F Regression 1 2.7500 -d- -e- 0.632 Residual -a- -b- 11.45 Total 14 -c- A Company has recorded data on daily demand for its product (y in thousands of units) and the unit price (x in hundreds of dollars). A...
#1 In simple linear regression, r is the: a) coefficient of determination. b) mean square error. c) correlation coefficient. d) squared residual. #2 In regression analysis, with the model in the form y = β0 + β1x + ε, x is the a) estimated regression equation. b) y-intercept. c) slope. d) independent variable. #3 A regression analysis between sales (y in $1,000s) and advertising (x in dollars) resulted in the following equation. ŷ = 40,000 + 3x The above equation...
Linear Regression and Prediction perform a linear regression to determine the line-of-best fit. Use weight as your x (independent) variable and braking distance as your y (response) variable. Use four (4) places after the decimal in your answer. Sample size, n: 21 Degrees of freedom: 19 Correlation Results: Correlation coeff, r: 0.3513217 Critical r: ±0.4328579 P-value (two-tailed): 0.11837 Regression Results: Y= b0 + b1x: Y Intercept, b0: 125.308 Slope, b1: 0.0031873 Total Variation: 458.9524 Explained Variation: 56.6471 Unexplained Variation: 402.3053...
3. Consider simple linear regression model yi = Bo + B12; + &; and B. parameter estimate of the slope coefficient Bi: Find the expectation and variance of 31. Is parameter estimate B1 a) unbiased? b) linear on y? c) effective optimal in terms of variance)? What will be your answers if you know that there is no intercept coefficient in your model?
please help! Following is a simple linear regression model: y = a + A + & The following results were obtained from some statistical software. R2 = 0.523 Syx (regression standard error) = 3.028 n (total observations) = 41 Significance level = 0.05 = 5% Variable Interecpt Slope of X Parameter Estimate 0.519 -0.707 Std. Err. of Parameter Est 0.132 0.239 Note: For all the calculated numbers, keep three decimals. Write the fitted model (5 points) 2. Make a prediction...
In a simple linear regression model, the slope term is the change in the mean value of y associated with _____________ in x. a corresponding increase a variable change no change a one-unit increase
We were unable to transcribe this imageD. b. Does a simple linear regression model appear to be appropriate? Explain. ;the relationship appears to be curvilinear Yes c. Develop an estimated regression equation for the data that you believe will best explain the relationship between these two variables. (Enter negative values as negative numbers). Several possible models can be fitted to these data, as shown below x + X2 (to 3 decimals) What is the value of the coefficient of determination?...
6. In multiple regression analysis, the word linear in the term "general linear model" refers to the fact that a. Bo, Bi, ... Bp, all have exponents of 0 b. Bo, Bi,... Bp, all have exponents of 1 c. Bo, B1, ... Bp, all have exponents of more than 1 d. B, B1, ... Bp, all have exponents of less than 1 7. The following model y = Bo + BX1 + E is referred to as a a. curvilinear...
Q9. In a simple linear regression model, the slope term is the change in the mean value of y associated with _____________ in x. A) a corresponding increase B) a variable change C) no change D) a one-unit increase
In a simple linear regression, the following information is given: x−x− = −39; y− y− = 40; Σ(xi−x− )(yi− y−)= −840;Σ(xi−x− )(yi− y−)= −840; Σ(xi− x−)2= 718Σ(xi− x−)2= 718 a. Calculate b1. (Negative value should be indicated by a minus sign. Round your answer to 2 decimal places.) b1 b. Calculate b0. (Round intermediate calculations to 4 decimal places and final answer to 2 decimal places.) b0 c-1. What is the sample regression equation? (Negative value should be...