INSTRUCTIONS FOR TOP ASSIGNMENT EXPERT
· Please answer ALL questions, they are numbered/lettered in PURPLE TEXT
· Note that some questions may need you to download the mentioned data .csv and perform an analysis (Use any method you need to perform this, like R or Excel, etc)
· Answers in American English – 500 words total
· Open format, simply answer each question
1. What is an outcome variable in a survey project? What is its purpose?
2. What is a screening question in a survey project? What is its purpose?
3. What are product attributes and how are they used in the typical marketing research survey?
1. How is a bar chart of two variables related to the table of joint frequencies, the cross-tabulation table?
2. Distinguish between a stacked bar chart of two variables and the co
esponding bar chart with the bars for each level grouped adjacent to each other.
3. What information does a marginal frequency present in the analysis of a joint frequency table?
4. Distinguish between positive and negative co
5. What is the relation between the amount of scatter in a scatter plot and the co
6. What is the relation of an ellipse to the scatter in a scatter plot?
7. What is the null hypothesis and its alternative for testing a co
8. What is the purpose of the confidence interval of a co
elation coefficient and what does it estimate?
1. Cross-Tabulation (from data)
A motorcycle clothing company needs guidance as to how many different jackets of each type to
ing to a motorcycle rally, a gathering of motorcyclists of a specific
and, BMW or Honda motorcyclists. The data are recorded from past sales of motorcycle jackets to owners, including the type of motorcycle. The jackets are of three types: Lite, Medium and Thick.
How do type of jacket and type of motorcycle relate? [The lessR bar chart function BarChart(), or bc(), provides the needed table and graph, as shown in Sec 7.2a of the posted readings. Track C students can use Excel, though BarChart() is easier if you followed the Week 1 R instruction content.]
Describe the data
a. What are the variable names?
. Are each of these variables continuous or categorical? Why?
c. Describe the values for each of the variables. List their values.
Relation between two variables
Describe the distribution of jacket types for the different motorcycle types together with a(n) ...
d. Visualization, stacked bar chart (show)
e. Visualization, grouped bar chart (show)
f. Cross-tabulation table (show)
g. How many motorcycle riders are in the sample? What combination of Jacket and Bike produced the lowest number of riders? The highest?
100% stacked bar chart
i. Show the 100% stacked bar chart.
j. For BMW riders, what percentage of customers purchased Lite, Med, and Thick Jackets? Same analysis for Honda riders.
k. If the vendor expects to sell 100 jackets at a Honda motorcycle rally, how many of each type do you recommend be
ought to the rally? Why?
elation Coefficient and Scatter Plot
The following data set contains data regarding university and percentage of graduates employed, tuition costs and general rating of prestige (real data).
Consider the relationship between % of graduates employed after graduation (EmpPct) and Tuition.
a. Construct the scatterplot with the .95 data ellipse. [You can still use a function called ScatterPlot, but now the direct reference is just Plot.]
. Report the sample co
elation coefficient. [Sec 8.1, #30]
c. Briefly describe the relationship. Is it positive or negative or neither? Why? [Sec 8.1, #2]
d. Specify the null hypothesis and alternative hypothesis for the hypothesis test of the slope coefficient of no relation.
[Answer with respect to the specifics of this analysis, e.g., the actual name of the variable, or an a
eviation, in this specific analysis, Sec 8.1, #28]
e. Report the p-value and statistical decision.
[specific with the numbers from this analysis as to the evaluation of the null hypothesis; Sec 8.1, #31]
f. Interpret the hypothesis test.
[applied to the relevant numbers of this specific analysis, with no jargon like p-value or t-value; Sec 8.1, #31]
g. What is the value that the confidence interval estimates?
[do not provide the confidence interval, which is the estimate not the value estimated; Sec 8.1, #28]
h. Interpret the confidence interval.
[no jargon, which includes “null hypothesis” and t-values, nothing about hypothesis tests; Sec 8.1, #31]
i. What do you conclude about spending money for college tuition and getting employed?
j. What is the distinction between your conclusion here from the conclusion from the descriptive statistics in c?
3. Analysis of Two-Variable Relationships
In Week 4 we analyzed the relationship between two variables with one method, and this cu
ent week, Week 7, we examined two more methods that each evaluate the relationship between two variables.
a. List the three statistical methods.
. Provide an example in terms of the types of variables applicable to each of these methods.