Question

MARKETING RESEARCH

In regression, the t-test assesses how far the beta coefficient is from 0. How does the minimum required t-value of 1.96 relate to the Three Sigma Rule of a normal distribution?

Answer #1

1. Compute the regression equation (regression coefficient and
constant) using the same data from the previous question. Compute
the explained variance (R Square) and the standardized regression
coefficient (beta) for this model. For R Square, Sums of Squares
Explained = 235.944; Sums of Squares Total = 520.
2. Given: sample R Square 0.232; SS explained = 2848.62; SS
residual = 9425.25; N = 62. Test the hypotheses Ho: R square = 0;
Ha: R square NE 0 at the .05...

The "beta coefficient" of a stock is a measure of the stock`s
volatility (or risk) relative to the market as a whole. Stocks with
beta coefficients greater than 1 generally bear greater risk (more
volatility) than the market, whereas stocks with beta coefficients
less than 1 are less risky (less volatile) than the overall market.
A random sample of 15 high-technology stocks was selected at the
end of 2009, and the sample mean and sample standard deviation of
the beta...

Given the following regression output,
Predictor
Coefficient
SE Coefficient
t
p-value
Constant
84.998
1.863
45.62
0.000
x1
2.391
1.200
1.99
0.051
x2
-0.409
0.172
-2.38
0.021
Analysis of Variance
Source
DF
SS
MS
F
p-value
Regression
2
77.907
38.954
4.138
0.021
Residual Error
62
583.693
9.414
Total
64
661.600
answer the following questions:
Write the regression equation. (Round your answers to 3
decimal places. Negative amounts should be indicated by a minus
sign.)
y= ____________ + _______________x1 + ________________
x2...

Suppose that a researcher, using data on class size (CS) and
average test scores from 50 third-grade classes, estimates the OLS
regression ModifyingAbove TestScore with caret equals 672.315 +
left parenthesis negative 5.1765 right parenthesistimesCS, Upper R
squared = 0.09, SER = 9.1 (24.675) (2.0806) Construct a 95%
confidence interval for beta 1, the regression slope coefficient.
The 95% confidence interval for beta 1, the regression slope
coefficient, is ( nothing, nothing). (Round your responses to
two decimal places.) The...

The following output comes from regression using the actual HW9
scores and the test scores from an introductory class taught three
years ago.
Sample size: 48
R (correlation coefficient) = 0.4961
R-sq = 0.24614276
Estimate of error standard deviation: 14.458866
Parameter estimates:
Parameter
Estimate
Std. Err.
DF
T-Stat
P-Value
Intercept
47.97618
5.5324807
46
8.671731
<0.0001
Slope
0.3491367
0.090088144
46
3.8755014
0.0003
Statistical Hypotheses:
Alpha level:
Critical value of z:
Conclusion regarding the null:
Conclusion in context of the situation:
Everybody...

Determine which SPSS statistical test is supposed to be used for
the following marketing research questions:
(Crosstabulation + Chi Square, One Sample t-test, Independant
t-test, Paired Sample t-test, ANOVA + Post Hoc)
Is there an association between how participants feel about the
content on social media and their gender?
In this study the feelings about
social media content investigated were: (a) anger, (b) inspiration,
(c) amusement, (d) depression, (e) connection and (f) loneliness.
These are measured on an ordinal scale....

Use a t-distribution and the given matched pair sample
results to complete the test of the given hypotheses. Assume the
results come from random samples, and if the sample sizes are
small, assume the underlying distribution of the differences is
relatively normal. Assume that differences are computed using
d=x1-x2.
Test H0 : μd=0 vs Ha : μd>0 using the paired data in the
following table:
Situation 1
120
156
145
175
153
148
180
135
168
157
Situation 2
120...

The following regression output was obtained from a study of
architectural firms. The dependent variable is the total amount of
fees in millions of dollars.
Predictor
Coefficient
SE Coefficient
t
p-value
Constant
9.387
3.069
3.059
0.010
x1
0.232
0.204
1.137
0.000
x2
−
1.214
0.584
−
2.079
0.028
x3
−
0.273
0.424
−
0.644
0.114
x4
0.642
0.362
1.773
0.001
x5
−
0.060
0.028
−
2.143
0.112
Analysis of Variance
Source
DF
SS
MS
F
p-value
Regression
5
2,364.50
472.9...

The marketing manager of a firm that produces laundry products
decides to test market a new laundry product in each of the firm's
two sales regions. He wants to determine whether there will be a
difference in mean sales per market per month between the two
regions. A random sample of 17 supermarkets from Region 1 had mean
sales of 86.2 with a standard deviation of 8. A random sample of 13
supermarkets from Region 2 had a mean sales...

The marketing manager of a firm that produces laundry products
decides to test market a new laundry product in each of the firm's
two sales regions. He wants to determine whether there will be a
difference in mean sales per market per month between the two
regions. A random sample of 12 supermarkets from Region 1 had mean
sales of 72.4 with a standard deviation of 6.2. A random sample of
16 supermarkets from Region 2 had a mean sales...

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