Question

1. Pick a minimum of 20 observations on any subject. This will include a dependent variable plus two independent variables that you may think are either negatively or positively correlated with the dependent variable. List the observed data (include the source). Then do the following:

a. State before doing any calculations whether you think they are positively or negatively correlated. What is your rationale?

Example: I test for a correlation between the quantity of coffee that people buy (Y) with the price of coffee (X1) and the household income (X2).

I hypothesize that there is a negative correlation between quantity and price because people like to buy goods at lower rather than higher prices. I also hypothesize that there is also a positive correlation between the quantity of coffee and household income because people can buy more coffee when their income increases.

b. Draw a graph of each of the two independent variables with the dependent variable either by hand or by using Excel. (Do this by inserting an XY/Scatter chart.)

c. Use Excel to do the necessary regression. Give the values for the y-intercept, b1, and b2. Write out the equation. Also show R-square, the F-statistic and its p-value and the t-statistics with their respective p-values.

d. Test for multicollinearity using the rule that the two independent variables are multicollinear if their correlation coefficient is .70 or greater (implying r-square is .49 or greater). If they are multicolliear, give a brief statement on why do you think that is the case.

e.Pretend that this was an assignment from your manager and communicate your findings to the manager in 100 words or less. You should assume in preparing this memo:

- Your manager is not familiar with statistical terminology. So if you use terms like R- square or t-statistic, you need to explain what they mean.

Answer #1

Regression: First, choose any metric variable as the dependent
variable and then choose any three other metric variables as
independent variables. HOWEVER, this process must be repeated until
you find a model that produces a significant F-calc (p-value (sig)
<.05). Thus, you may have to sort through several combinations
of dependent and independent variables before finding a combination
that produces a significant F-calc. This is actually quite easy to
do in SPSS using the drop down menus as shown in...

I
have two regression models.
same independent variable and same control variables in
both.
The only diferrence is the dependent variable.
in my findings what do I discuss? my AR 2 for one is .267 and
the other is .046.
in my findings do I talk about the difference between the
adjusted r square value?
thank you!

You have estimated the correlation between exposure to
noise (independent variable) and hearing loss (dependent variable)
among factory workers. Both exposure and outcome measures were
collected as continuous variables. The statistical analysis showed
a Pearson r of 0.4 and the correlation between the
two variables was highly significant at p < 0.001.
Question: Can one argue that the
relationship between the investigated exposure and outcome is
causal? why and How likely is the possibility that the results were
a mere chance finding? Why?...

SUMMARY OUTPUT
Dependent
X variable:
all other variables
Regression Statistics
Independent
Y variable:
oil usage
Multiple R
0.885464
R
Square
0.784046
variation
Adjusted R Square
0.76605
Standard Error
85.4675
Observations
40
ANOVA
df
SS
MS
F
Significance F
Regression
3
954738.9
318246.3089
43.56737
4.55E-12
Residual
36
262969
7304.693706
Total
39
1217708
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Lower 95.0%
Upper 95.0%
Intercept
-218.31
63.95851
-3.413304572
0.001602
-348.024
-88.596
-348.024
-88.596
Degree Days
0.275079
0.036333
7.571119093
5.94E-09...

Consider the following results of a multiple regression model of
dollar price of unleaded gas (dependent variable) and a set of
independent variables: price of crude oil, value of S&P500,
price U.S. Dollars against Euros, personal disposal income (in
million of dollars) :
Coefficient
t-statistics
Intercept
0.5871
68.90
Crude Oil
0.0651
32.89
S&P 500
-0.0020
18.09
Price of $
-0.0415
14.20
PDI
0.0001
17.32
R-Square = 97%
What will be forecasted price of unleaded gas if the value of
independent...

4) Suppose you want to find out if there is a relationship
between anxiety and sleep deprivation. So you go out and find 7
people and measure how much anxiety they are experiencing in their
lives and how many hours of sleep they are getting.
Let X be the explanatory variable to describe anxiety, you
obtain the following values for X in order from subject 1 to
subject 7: 1, 2, 4, 4, 5, 8, 7 Let Y be the...

This Question has 6 parts.
Variability within groups in an ANOVA reflects any potential
effect of a “treatment” among different groups.
True
False
If the null hypothesis is true in a two variable chi-square
test, the expected values will always be the same as the observed
values.
True
False
A two variable chi-square test is also known as a “goodness of
fit” test.
True
False
The Ŷ in a regression equation represents the “predicted” value
of Y, when a chosen...

For each of the studies, please indicate the
following:
1)Independent variable
True/Quasi?
2)Is there more than one
IV?
3) The levels of the independent
variable
4) Dependent variable
5) the level of measurement (NOIR) of the DV
6) Between (BS) or within-subjects (WS)?
7) What type of design is being used?
8) What is the appropriate statistic? (for correlation list all
variables)
Study 12: A researcher is interested in the
relationship between socio-economic status and domestic violence.
She believes that...

For each analysis, write out the null hypothesis, explain what
the analysis is looking at, calculate anything you think needs
calculating (like expected cell counts), identify whether you think
the null is right, and then tell the manager what the results
mean.
10. Oneway ANOVA
Type of Business Student
Freshman (1)
Sophomore (2)
Junior (3)
Senior (4)
Average Perceived Challenge
4.2
4.7
3.6
4.2
Source
Variation
F
p
Between Groups
5.89
1.89
.76
Within Groups
254.3
Total
260.19
Post hoc...

Use the dependent variable (labeled Y) and the independent
variables (labeled X1, X2, and X3) in the data file. Use Excel to
perform the regression and correlation analysis to answer the
following.
Generate a scatterplot for the specified dependent variable (Y)
and the X1 independent variable, including the graph of the "best
fit" line. Interpret.
Determine the equation of the "best fit" line, which describes
the relationship between the dependent variable and the selected
independent variable.
Determine the coefficient of...

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