Pricing analysis for a customizable beverage delivery service
This order consists of two files. First, Part I is n both a Word and Excel File. This represents a series of graphs and analysis off of a proposed product that was asked by 25 participants to gauge the price. It represents price data for both 12 and 24 packs. The rest of the Word document is the answers to a series for statistical questions that were in Part II.
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Product Definition
Everyone who has been to college knows how difficult shopping can be with roommates. The fact of the matter is that no one agrees on anything. What happens is that often times, college students have to buy sodas in bulk, thinking they will be saving money; but, because only some people in their household actually like certain flavors, there is a lot of waste. The product here is actually a beverage delivery service that provides 12 and 24 packs of beverages or sodas, all with unique flavor combinations upon order request. The customers can go online and order whatever number of particular flavors they want, allowing them to mix and match in order to create a bulk discount that all the members of their household can enjoy.
Data Table
Data
Subject
Price 12 pk
Price 24 pk
1
2
9
15
3
8
4
5
6
7
8
9
10
5
11
11
12
6
13
14
11
15
4.5
9.99
16
8
12.99
17
6.99
10
18
5.99
11
19
4.99
8.99
20
5.5
10
21
6.5
11.99
22
7.99
13
23
5.5
9.99
24
4.5
8.99
25
6.5
Intervals
Number of Bins and Intervals
6 bins of 5 Intervals each to make up the answers for both 12 pack and 24 packs
Data Intervals
Frequency Chart
Frequency Chart (12 Pack)
Class Interval
Frequency
0-5
2
5.01-10
21
10.01-15
0
15.01-20
0
20.01-25
0
Frequency Chart (24 Pack)
0-5
0
5.01-10
5
10.99-15
15
15.01-20
1
20.01-25
0
Histogram
12 Pack Prices
24 Pack Prices
Frequency Polygon
Analysis
The data collected really helps me be able to price the product, in both 12 and 24 pack varieties. It is important to understand how frequency contributes to consumer demand (Cartlidge & Phelps, 2010). I get a general idea of what people would be willing to spend for a more specialty beverage product, and helps me assume what the average frequency would be, which can be compared to the price point made through the mark up after understanding the value chain analysis and the costs of operating per pack, either 12 or 24 beverages. Frequency and data intervals must be appropriate to the data provided, or else there is nothing gained from the testing (Lind et al., 2004).
I did learn a lot about data collection. I learned that it is important to really take advantage of statistical analysis in order to understand the consumer market. The analysis here allows me to see what consumer expects to pay (Citizens Information, 2011). This can then be compared to what I would need to mark unit prices up based on the cost I would be paying per unit. The two need to correlate in order for me to make a profit on the product (Gopinath & Itskhoki, 2009).
Part II
Topic 9, Exploration 6
a. At 4% interest, the monthly payment would be $253.50 a month for a total of $80,002.69 at the end of 18 years.
b. At 7% interest, the monthly payment would be $185.75 for a total savings of $80,006.43.
c. At 9% interest, the monthly payment would be $149.20 for the full length for a total savings of $80,023.67.
Scatterplot with lines
b. The Date and Year data should be on the horizontal line axis. This is because it is more wide spread, which allows for the scatter plot graphs to be more spread out and visible.
C. There are not enough variables in order to really show a good picture of the scatterplot. More years should be shown, with less gaps in between them.
Activity 6.2
b. 6 points lie above the line
c. 5 points lie below the line
d. The slope of the line is positive because it is going upwards in the right quadrant.
Regression Analysis for SAT Data
Here, the X variable represents the critical reading score, while the Y variable represents the percent of the population who took the test.
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