The below report presents the detailed statistical analysis of the data collected from a sample of credit customers in the department store “AJ DAVIS Departmental stores”.

The 1st individual variable considered is Location. It is a category variable. The three subcategories are Urban, Suburban and Rural. Category variable, the measures of central tendency and descriptive statistics has not been calculated for this variable. The frequency distribution and pie chart are below:

From the frequency distribution and pie chart, it is display the maximum number of customers belongs to the rural category (42%), suburban category (30%) and Only 28% of the customers belong to the urban category.

The 2nd individual variable considered is Size. It is a quantitative variable. The measures of central tendency, variation and other descriptive statistics have been calculated for this variable are below:

...Statistical Report
The Relationships between Location, Income, and Credit Balance for the customers of AJ Davis Department Store
Math533
Course Project Part A
AJ DAVIS DEPARTMENT STORES
AJ Davis Department Store Customer Research
A. Brief Introduction
The department store AJ Davis would like to find out more information about their customers. A sample of 50 credit customers is selected with data collected on the following five variables:
1. LOCATION (Rural, Urban, Suburban)
2. INCOME (in $1,000's – be careful with this)
3. SIZE (Household Size, meaning number of people living in the household)
4. YEARS (the number of years that the customer has lived in the current location)
5. CREDIT BALANCE (the customers current credit card balance on the store's credit card, in $).
This report presents the findings of three individual variables extensively which include location, income, and credit balance. We will also discuss three pairing of variables extensively which include: location and income, income and credit balance, as well as location and credit balance. These variables and pairings will give AJ Davis the most information about their customers.
B. 1st Individual Variable is location:
Location is very important to AJ Davis because knowing where your customers come from is the basis for most of your research. From location you can draw a correlation with every variable....

...histogram graph has a wider bell shape form. The skewness of this graph is skewed right. Size has a lower value of kurtosis which indicates a lower, less distinct peak. The following table shows the numerical summary of Income.
Descriptive Statistics: Size
Total
Variable Count N N* CumN Percent CumPct Mean SE Mean TrMean StDev Variance
Size 50 50 0 50 100 100 4.500 0.357 4.500 2.525 6.378
Sum of
Variable CoefVar Sum Squares Minimum Q1 Median Q3 Maximum Range IQR
Size 56.12 225.000 1325.000 1.000 2.000 4.500 7.000 8.000 7.000 5.000
N for
Variable Mode Mode Skewness Kurtosis MSSD
Size 1, 8 8 0.00 -1.49 2.969
The P-value of the Size using the Anderson-Darling Normality Test is .005 and the A-Squared is 1.59. With the 95% Confidence Interval for Mean, Median, and St Dev are as described above.
This graph shows that the size of two people per household is much higher than others.
E. Discuss your 1st pairing of variables, using graphical, numerical summary and interpretation
Total
Variable Location Count N N* CumN Percent CumPct Mean SE Mean TrMean
Income ($1,000) Rural 13 13 0 13 26 26 37.54 2.24 37.27
Suburban 15 15 0 28 30 56 47.27 3.91 47.31...

...the rual areas totaling 42%
The Second will be the size chart. This will measure tendency, variation, mean, median and mode.
Descriptive Statistics:
Size
Mean 3.42
Standard Error 0.24593014
Median 3
Mode 2
Standard Deviation 1.73898868
Sample Variance 3.02408163
Kurtosis -0.7228086
Skewness 0.52789598
Range 6
Minimum 1
Maximum 7
Sum 171
Count 50
Frequency Distribution:
Size Frequency
1 5
2 15
3 8
4 9
5 5
6 5
7 3
The mean household size of the customers is given as 3.42. The median of the data is 3 and the mode is 2. The standard deviation is given approximately as 1.74. Maximum number of customers has a household size of 2 as is evident from the frequency distribution and the bar graph.
The Third chart is over credit Balance.
Descriptive Statistics:
Credit Balance($)
Mean 3964.06
Standard Error 132.0159991
Median 4090
Mode 3890
Standard Deviation 933.4940816
Sample Variance 871411.2004
Kurtosis -0.741830067
Skewness -0.129506489
Range 3814
Minimum 1864
Maximum 5678
Sum 198203
Count 50
Relative Frequency Distribution:
Credit Balance ($) Frequency Relative Frequency
1500 - 2000 1 0.02
2000 - 2500 2 0.04
2500 - 3000 6 0.12
3000 - 3500 6 0.12
3500 - 4000 8 0.16
4000 - 4500 12 0.24
4500 - 5000 7 0.14
5000 - 5500 6 0.12
5500 - 6000 2 0.04
The mean credit balance of the customers is given as $3964.06. The standard deviation is 933.49. The credit balance of...

...using a mathematical formula that accounts for a person’s height and weight. BMI is equal to a person’s weight in kilograms (kg) divided by height in meters squared (BMI=).
Aim
The aim of this project work is to investigate the relationship between height, weight and BMI with students’ health condition. The purpose of this campaign is to create awareness among students about obesity or underweight related to health problems. We should select an appropriate balanced diet to avoid from being a victim to such illness. Nutritional guidelines play an important role in helping us to make informed choices about our nutrient intake. The foods that constitute a balanced diet should contain the major nutrients which include carbohydrates, proteins and lipids, as well as vitamins, minerals, water and dietary fibre. A balanced diet is essential for the healthy growth and development of the body.
The objectives of carrying out this project work are:
1 To collect data on the heights and weights of students.
2 To calculate BMI of each students.
3 To represent data using various methods.
4 To relate students’ knowledge with the data obtained.
5 To suggest ways to practice healthy lifestyle.
The methods of research are as follows:
1 To obtain the height, weight and BMI of 50 students in Form 1 and 50 students in Form 5.
2 To tabulate the data consisting the height, weight and BMI of this 100 students.
3...

...
Course Project Part Three
Professor Douglas Nottingham
March 27, 2014
1. Generate a scatterplot for CREDIT BALANCE vs. SIZE, including the graph of the "best fit" line. Interpret.
The larger the size of the family the larger the credit balances is for the family. The larger families have the financial needs to have a larger credit balance.
2. Determine the equation of the "best fit" line, which describes the relationship between CREDIT BALANCE and SIZE.
Credit Balance ($) = 2591 + 403.2 Size
3. Determine the coefficient of correlation. Interpret.
The square root of R-Squared = .566 equals R; R = .75
4. Determine the coefficient of determination. Interpret.
The R-Squared is .566. The R-Squared is stating that 56.6% of the data is correct which indicates that the percentage of the total sample variation of the credit balance value is accounted for by the model.
5. Test the utility of this regression model (use a two tail test with α =.05). Interpret your results, including the p-value.
Regression Analysis: Credit Balance ($) versus Size
The regression equation is
Credit Balance ($) = 2591 + 403 Size
Predictor Coef SE Coef T P
Constant 2591.4 195.1 13.29 0.000
Size 403.22 50.95 7.91 0.000
The p-value is 0.000 and therefore less than the α=.05 and we reject the Ho because there was not enough evidence too.
6. Based on your findings in...

...Math533Project Part B
In regards to the dataset from AJ Department store, your manager has speculated the following:
the average (mean) annual income is less than $50,000,
the true population proportion of customers who live in an urban area exceeds 40%,
the average (mean) number of years lived in the current home is less than 13 years,
the average (mean) credit balance for suburban customers is more than $4300.
Part 1. Using the sample data, perform the hypothesis test for each of the above situations in order to see if there is evidence to support your manager’s belief in each case a.-d. In each case use the Seven Elements of a Test of Hypothesis, in Section 6.2 of your text book with α = .05, and explain your conclusion in simple terms. Also be sure to compute the p-value and interpret.
Our textbook tells us the following are the elements used to test a hypothesis:
Elements of a Test of Hypothesis
1. Null hypothesis (H0): A theory about the specific values of one or more population parameters. The theory generally represents the status quo, which we adopt until it is proven false. The theory is always stated as H0: parameter = value.
2. Alternative (research) hypothesis (Ha): A theory that contradicts the null hypothesis. The theory generally represents that which we will adopt only when sufficient evidence exists to establish its truth.
3. Test...

...Fractions
IB Math SL
SL Type 1
December 11, 2012
Lacsap’s Fractions:
Lacsap is Pascal backwards and the way that Lacsap’s fractions are presented is fairly similar to Pascal’s triangle. Thus, various aspects of Pascal’s triangle can be applied in Lacsap’s fraction.
To determine the numerators:
To determine the numerator (n), consider it in relation to the number of the row (r) that it is a part of.
Consider the five rows below:
Row 111
Row 2 1 32 1
Row 3 1 64 64 1
Row 4 1 107 106 107 1
Row 5 1 1511 159 159 1511 1
The relation between the numerator and the row number can be shown by the equation:
Where the numerator = n
And the row = r
0.5r2 + 0.5r = the numerator (n)
When r=1
0.5(12) + 0.5(1) = 1
When r=2
0.5(22) + 0.5(2) = 3
When r=3
0.5(32) + 0.5(3) =6
When r=4
0.5(42) + 0.5(4) = 10
When r=5
0.5(52) + 0.5(5) = 15
Therefore if you are attempting to find the 6th or 7th row numerators, you simply plug (n) into the equation:
When r=6
0.5(62) + 0.5(6) = 21
When r=7...