Topic 2 Discussion
Statistics
Professor Powell
Part 1
I’m actually really thankful that this was part of the assignment because honestly I would not
have looked into these resources otherwise. The multimedia library hosts a selection of different
ways to read and interpret the data and information from specific chapters and sections. The
options include the multimedia textbook, videos, videos from EACH section, Java applets,
PowerPoints, and StatCrunch, which is kind of like excel.
Part 2
Data: 24, 26, 27, 27, 28, 31, 34, 35, 36, 39, 40, 43, 43, 45, 51
Number of classes: 5
Class width: (max-min)/class #= (51-24)/5= 5.6=> 6
Classes
Frequency
Relative Frequency
24-29
5
1/3 or .33 or about 33%
30-35
3
1/5 or .2 or 20%
36-41
3
1/5 or .2 or 20%
42-47
3
1/5 or .2 or 20%
48-53
1
1/15 or .066% or about 7%
There are no outliers because all the numbers in the data set are close together.
[24-29]
[30-35]
[36-41]
[42-47]
[48-53]

30
th
percentile: 28. This means that 30% of all the data has a value of 28 or less.
5 number summery: 24, 27.5, 35, 41.5, 51
Part 3
2
4 6 7 7 8
3
1 4 5 6 9
4
0 3 3 5
5
1
This data has a positive skew to the right
Part 4
Scenario: Desserts sold in a bakery over 10 days
Data: (1,27) (2,34) (3,15) (4,40) (5,25) (6,19) (7,47) (8,36) (9,21) (10,34)
2
4
6
8
10
12
5
10
15
20
25
30
35
40
45
50
Desserts Sold in a Bakery Over 10 Days
Day
Desserts Sold
Line of regression: 0.558x+26.733
In this case the y intercept is unreasonable because “0” does not count as a day and
therefore the number of desserts sold on day 0 is not interpretable.
The slope of the line is very small which depicts that there is a very slight positive
ascension as more days go by.
r= 0.1672
R^2= 0.028
Line of regression
0.558x+26.733