QUESTION A: A regression was run to determine if there is a
relationship between hours of TV watched per day (x) and number of
situps a person can do (y).
The results of the regression were:
y=a+bx
a=26.695
b=-0.65
r2=0.531441
r=-0.729
Assume the correlation is significant (p-value < α), and use
this to predict the number of situps a person who watches 13.5
hours of TV can do (to one decimal place)
QUESTION PART B: Run a regression analysis on...
Determine the regression equation (write the regression
equation) of the following data, where Y is the dependant variable
and X is the predictor:
X
Y
5
85
4
103
6
70
5
82
5
89
5
98
6
66
6
95
2
169
7
70
7
48
b) Interpret the regression coefficients.
c) Graph the regression line.
d) Use the regression equation to predict Y for
X=3.
e) Compute the coefficient of
determination.
f) Interpret the coefficient of
determination.
g)...
Run a linear regression using Excel’s Data Analysis regression
tool. Construct the linear regression equation and determine the
predicted total sales value if the number of promotions is 6. Is
there a significant relationship? Clearly explain your reasoning
using the regression results.
Number of Promotions
Total Sales
3
2554
2
1746
11
2755
14
1935
15
2461
4
2727
5
2231
14
2791
12
2557
4
1897
2
2022
7
2673
11
2947
11
1573
14
2980
Curve Fitting and Linear Regression
a) Determine the linear regression equation
for the measured values in the table above.
??
1
2
3
4
Value 1 (????)
0
3
7
10
Value 2 (????)
2
4
9
11
b) Plot the points and the linear
regression curve.
c) Determine the Linear Correlation
Coefficient (i.e., Pearson’s r) for the dataset in the
table above.
Regression Analysis (use Excel)
Need to determine if there is a relationship in the amount a
household spends on prepared foods to family size and income. Need
to be able to answer if the data is a good fit and what the exact
relationship is between the dependent variable and the independent
variables. Please use the below data and Excel to determine the
equation that represents the relationship and explain the goodness
of fit. Based on the data, how might...
Question 3 Determine the equation of the regression line for the
following data, and compute the residuals. x 15 9 20 11 4 y 48 35
55 44 18 Do not round the intermediate values. (Round your answers
to 3 decimal places.) Do not round the intermediate values. (Round
your answers to 3 decimal places.) x y Residuals 15 48 9 35 20 55
11 44 4 18
I
am trying to run a regression in R with a continuous dependent
variable and a binary independent variable? The binary one refers
to whether a person received treatment or not. how do I interpret
the regression outputs since I dont get results based 0 or 1 buf
the whole variable?