Business Analytics - MIDTERM

CME Group Foundation Business Analytics Lab

Question 1: Read in the gambling dataset check the first couple of rows and describe the data types. Identify incorrect data types, if any. ( 5 Points )

mydata = read.csv(file="data/gambling.csv")
head(mydata)

Question 2: Describe the data using full sentences and using descriptive statistics. ( 5 Points )

The gambling data shows the gender of the player, the status, their income, their verbal signs, and their gambling rate.

Question 3: Estimate the upper and lower threshold for the verbal score ( 5 Points )

verbal = mydata$verbal
verbal

 [1]  8  8  6  4  8  6  7  5  6  7  6  6  4  6  6  8  8  5  8  9  8  9  5  4  7  7  4  6  7  8
[31]  2  7  7 10  1  8  7  6  6  6  9  9  8  9  6  7  9

verbalmean = mean(verbal)
verbalmean
verbalsd = sd(verbal)
verbalsd

lowerverbal = verbalmean -(3 * verbalsd)
upperverbal = verbalmean + (3 * verbalsd)
lowerverbal

[1] 1.0899

upperverbal

[1] 12.22925

Question 4: Calculate the z-score for income where x=13. Based on the income value x=13 pounds per week, how would you rate the income: low income, average income, high income. Why? ( 5 Points )

income = mydata$income
income

Hint: zscore = (x - mean)/sd

incomemean = mean(income)
incomemean

[1] 4.641915

incomesd = sd(income)
incomesd

[1] 3.551371

zscore = (13-incomemean)/incomesd
zscore

[1] 2.353481

I would rate the z-score as average, because it is in the middle of all the income data points. The max being 7 and the lowest being 2.

Question 5: Create a histogram for the zscore of income. What do you notice about the shape? ( 5 Points )

Hint: To plot a histogram, use the function hist(variable).

hist(income)

hist

function (x, ...) 
UseMethod("hist")
<bytecode: 0x1024b9e38>
<environment: namespace:graphics>

hist(zscore)

hist

function (x, ...) 
UseMethod("hist")
<bytecode: 0x1024b9e38>
<environment: namespace:graphics>

Question 6: Analyze the correlation plot below. Give relavant information about the negative correlated, no correlared and positive correlated variables. ( 5 Points )

The benefits definitely outweigh the risks because the x axis is more prominent on the right. While there is frequent correlation, but many casual hypothesis, because the largest dots lie in the middle.

Extra Credit: Analyze the correlation table below. Give relavant information about the negative correlated, no correlared and positive correlated variables. ( 5 Points )

# Create a correlation table "cor(movies)"