Expert answer:MGMT 650 Fall 2017 Week 11 Homework (Last updated
Expert answer:Hello, I had a couple of assignments today, this is just one of them. They are not very hard. So please do not ask so much for this assignment. I still have many more please
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MGMT 650 Fall 2017 Week 11 Homework
(Last updated 7/11/2017)
work
1. Scatterplot and Correlation
Studies have shown that the frequency with which shoppers browse Internet retailers is related to the frequency
and/or services online. These data show the age of respondents and their answer to the question “How many mi
week?”
22
50
44
32
55
60
38
22
21
45
52
33
19
17
21
Browsing Time (min/wk)
492
186
180
384
120
120
276
480
510
252
126
360
570
588
498
Browsing Time against
700
browsing time(min/wk)
Age
600
500
400
300
200
100
0
0
10
20
30
a) Calculate the associated correlation coefficient and discuss how strong you think the relationship is between th
Correlation procedures within Excel under Data > Data Analysis.
b) Find the correlation coefficient using the Excel function CORREL.
c) Set up a scatter (xy) diagram with Age on the horizontal axis. Add the chart name and axes descriptions to your
d) Add a trendline to the diagram.
e) Find the equation of the regression line. (Hint: One way to do this is by adding the equation to the trendline. Go
f) Predict the number of minutes spent by a 40-year old shopper.
g) Can you use this data to predict the number of minutes spent by a 75 year old shopper? How about a 35 year o
elated to the frequency with which they actually purchase products
question “How many minutes do you browse online retailers per
wsing Time against age
y = -11.503x + 750.02
R² = 0.9679
30
40
50
60
70
Age
lationship is between the age and the browsing time. Use the
xes descriptions to your chart.
tion to the trendline. Go to format trendline and find it there).
? How about a 35 year old?
2. Regression and Correlation
An agent would like to predict the monthly rental cost for apartments, based on the size of the apartment, as defi
sample of 25 apartments in a particular residential neighborhood and gathers the data shown in the table.
Size (Square feet)Rent (Dollars)
850
950
1450
1600
1085
1200
1232
1500
718
950
1485
1700
1136
1650
726
935
700
875
956
1150
1100
1400
1285
1650
1985
2300
1369
1800
1175
1400
1225
1450
1245
1100
1259
1700
1150
1200
896
1150
1361
1600
1040
1650
755
1200
1000
800
1200
1750
a) Find the correlation coefficient. Is it strong or weak? Positive or negative?
Run the Regression function from the Data Analysis tools and use the results to answer the following questions:
b) Find the equation of the regression line.
c) Find the slope, and interpret its meaning.
d) Compute the coefficient of determination, R Square, and interpret its meaning.
e) Compute the standard error of estimate, and interpret its meaning.
he size of the apartment, as defined by square footage. The agent selects a
data shown in the table.
nswer the following questions:
3. Scatterplot
a)
X
6.981
3.982
2.084
9.113
2.280
6.567
1.897
7.186
4.094
1.257
7.199
2.136
3.032
3.735
8.612
0.338
5.348
9.208
7.570
8.646
1.953
3.475
3.962
8.084
4.866
Make an XY scatter plot linked to the following data on this sheet.
Y
12.266
8.455
5.951
14.395
7.435
11.332
7.011
12.716
9.214
7.499
10.473
6.124
8.832
9.295
34.622
7.155
10.475
13.650
13.910
11.895
7.387
7.871
10.482
11.727
8.688
b)
The scatterplot reveals an outlier. Copy the data to a new sheet or a new area on this sheet, and remove th
c)
Right click on the points, Add Trendline, Display Equation on chart, Display R-Squared value on chart
d)
Read the intercept directly from the chart equation label. The elevation of the line above the origin with
e)
Read the slope directly from the chart equation label. The slope of the line with 3 decimal places =
f)
So, when X increases by 1, the change in Y =
g)
Read R
2
directly from the chart equation label. The amount of the variation in Y explained by X in percen
yത
a on this sheet, and remove the outlier. You should now have 24 rows of data above. Make a new scatterplot from the revised data.
-Squared value on chart
he line above the origin with 3 decimal places =
with 3 decimal places =
in Y explained by X in percent is =
7/8/2017 18:19
Question #
4
Highlight the correct answer or answers for each of the following questions
Basic Theory
The best fitting line is found using advanced math to minimize the vertical distances from the points to the li
Hence, the Y coordinate of a point on the best fitting line provides an estimate of Y at the value of the corres
This process is called regression (to move backward) because
● The estimate of Y will be closer to the mean in standard deviations than X is.
● The estimate of Y will be farther from the mean in standard deviations than X is.
5
Highlight all assumptions requiring validation for linear regression and prediction
● Scatter plot pattern is reasonably straight (Linearity)
● No points lie far enough away to pull the line of best fit away from the main point pattern.
● The plot does not fan out as x increases or decreases (Equal Spread)
● Predict Y at a value of X within the range of the X data
6
The “intercept” and “slope” completely define the best fitting line.
The intercept is the vertical distance from the origin (where the X and Y axes intersect) up to the line. It sets
● TRUE
● FALSE
7
As the slope increases
● The line moves up
● The line moves down
● The line rotates clockwise
● The line rotates counterclockwise
8
R2 measures the fit of the line to the points. As R2 increases
● The scatter about the line increases and the amount of the variation of Y explained by X decreases
● The scatter about the line decreases and the amount of the variation of Y explained by X increases
● The scatter about the line increases and the amount of the variation of Y explained by X increases
● The scatter about the line decreases and the amount of the variation of Y explained by X decreases
9
The correlation R measures the linear dependence of Y on X, and does not have a unit of measure.
● True
● False
10
Highlight the 3 correct statements
● X denotes the independent or response variable
● X denotes the independent or explanatory variable
● Y denotes the dependent or explanatory variable
● Y denotes the dependent or response variable
● x denotes the observed value of the dependent variable
● y
ത denotes the mean value of observations of the response variable
tances from the points to the line.
e of Y at the value of the corresponding X coordinate
point pattern.
intersect) up to the line. It sets the elevation of the line
explained by X decreases
xplained by X increases
explained by X increases
xplained by X decreases
ave a unit of measure.
…
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