Q & A of the computer lab seminars
of MR2 including the plots, outputs
and graphs.
written by:
JorisAE
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Computer Lab Seminars
Week 1
Q: What is the label of the variable Type_cl? What are the possible values of this variable and
what is the meaning of each possible value? Does the data file indicate this variable is
nominal, ordinal or quantitative?
A: See the sheet Variable View in the data editor. The label is Client commitment.
The possible values are 1 = Low commitment, 2 = Medium commitment and 3 = High
commitment. The variable is ordinal.
Q: Make a frequency table of Type_cl. What is the relative frequency of “low commitment” in
the sample? What is the mode?
A: You can use Analyse, Descriptive Statistics, Frequencies.
client commitment
Frequency Percent Valid Percent Cumulative
Percent
Low commitment 24 34.3 34.3 34.3
Medium commitment 21 30.0 30.0 64.3
Valid
High commitment 25 35.7 35.7 100.0
Total 70 100.0 100.0
The relative frequency of Low commitment is 34.3%. The modal category is High commitment.
Q: Make a pie chart and a bar chart of Type_cl. In which of the two graphs is it easier to detect a
majority (coalition that covers more than 50%)? In which of the two graphs is it easier to see
the order of the categories?
A: You can use Analyze, Descriptive Statistics, Frequencies, and select Pie charts or Bar charts
under the button Charts.
If there are more than 2 categories:
‐ In the pie chart it is easier to detect a majority (coalition that covers more than 50%).
‐ In the bar chart it is easier to see the order of the categories.
Q: What is the full name, given in the label, of the variable Price_l? Make a stem‐and‐leaf plot
and a histogram of Price_l . What is the mode according to the histogram? What is the unit
of the stem and of the leaf? What is the mode according to the stem‐and‐leaf plot (similar to
the mode of a histogram)?
A: Price_l is labeled as Price Level. You can use Analyze, Descriptive Statistics, Explore.
of MR2 including the plots, outputs
and graphs.
written by:
JorisAE
The Marketplace to Buy and Sell your Study Material
Buy and sell all your summaries, notes, theses, essays, papers, cases, manuals, researches, and
many more..
www.stuvia.com
, Stuvia.com - The Marketplace to Buy and Sell your Study Material
Computer Lab Seminars
Week 1
Q: What is the label of the variable Type_cl? What are the possible values of this variable and
what is the meaning of each possible value? Does the data file indicate this variable is
nominal, ordinal or quantitative?
A: See the sheet Variable View in the data editor. The label is Client commitment.
The possible values are 1 = Low commitment, 2 = Medium commitment and 3 = High
commitment. The variable is ordinal.
Q: Make a frequency table of Type_cl. What is the relative frequency of “low commitment” in
the sample? What is the mode?
A: You can use Analyse, Descriptive Statistics, Frequencies.
client commitment
Frequency Percent Valid Percent Cumulative
Percent
Low commitment 24 34.3 34.3 34.3
Medium commitment 21 30.0 30.0 64.3
Valid
High commitment 25 35.7 35.7 100.0
Total 70 100.0 100.0
The relative frequency of Low commitment is 34.3%. The modal category is High commitment.
Q: Make a pie chart and a bar chart of Type_cl. In which of the two graphs is it easier to detect a
majority (coalition that covers more than 50%)? In which of the two graphs is it easier to see
the order of the categories?
A: You can use Analyze, Descriptive Statistics, Frequencies, and select Pie charts or Bar charts
under the button Charts.
If there are more than 2 categories:
‐ In the pie chart it is easier to detect a majority (coalition that covers more than 50%).
‐ In the bar chart it is easier to see the order of the categories.
Q: What is the full name, given in the label, of the variable Price_l? Make a stem‐and‐leaf plot
and a histogram of Price_l . What is the mode according to the histogram? What is the unit
of the stem and of the leaf? What is the mode according to the stem‐and‐leaf plot (similar to
the mode of a histogram)?
A: Price_l is labeled as Price Level. You can use Analyze, Descriptive Statistics, Explore.
