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MGMT 5504 : Data Analysis and Decision Making

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DATA ANALYSIS & DECISION MAKING (MGMT5504)

   

Added on  2020-05-11

MGMT 5504 : Data Analysis and Decision Making

   

DATA ANALYSIS & DECISION MAKING (MGMT5504)

   Added on 2020-05-11

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Factors affecting individual savings behavior
MGMT 5504 : Data Analysis and Decision Making_1
Table of Contents1.EXECUTIVE SUMMARY......................................................................................................22.INTRODUCTION....................................................................................................................23.ANALYSIS AND METHODS................................................................................................23.1.THE VARIABLES...........................................................................................................23.2.DESCRIPTIVE STATISTICS..........................................................................................33.3.CORRELATIONS BETWEEN VARIABLES.................................................................33.4.DETERMINING THE BEST MODEL............................................................................43.5.PREDICTION...................................................................................................................84.RECOMMENDATIONS.........................................................................................................8
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1.EXECUTIVE SUMMARY This paper assesses the factors that affect individual savings behavior. A sample of 100observations was collected from individuals in order to determine what factor affect thesavings of individuals. The variables were six in total (five explanatory variables and 1dependent variable). Results showed that out of the five explanatory variables, 3 weresignificantly related with the dependent variable (savings). 2.INTRODUCTIONIn this paper, we sought to present analysis on the factors that affect the savings power ofpersons. Analysis was done using Data Analysis Tool in excel. We 3.ANALYSIS AND METHODS3.1.THE VARIABLESThe following five variables were considered for inclusion in a multiple-regression modelto predict individual savings [Y]. The variables were: (1)Income: The individual’s income. [X1] (2)Family Size: The size of the family. [X2] (3)Education: Education level of the person. [X3] (4)Age: The age of the person. [X4] (5)Black: This is a dummy variable for race with “1” being black and “0” non-black.[X5] 3.2.DESCRIPTIVE STATISTICSWe began the analysis by analysis the descriptive statistics. Table 1 below gives thedescriptive statistics
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As can be seen, the average savings was found to be $1,582.51 while the average income$9,941.24. The average family size was 4.35 while the average education level was 11.58with the average age is 38.77 years old.Table 1: Descriptive statisticsSavingsIncomeFamilysizeEducationageMean2135.4809961.2404.35011.58038.770Standard Error300.317556.7860.1490.3440.740Median1205.5008776.5004.00012.00038.500Mode1389.000#N/A4.00012.00033.000Standard Deviation3003.1755567.8561.4933.4357.399Sample Variance9019059.12131001024.6082.23011.80254.745Kurtosis36.5615.5051.8080.175-0.904Skewness5.1402.0560.8630.0470.242Range25392.00031330.0008.00018.00028.000Minimum13.000750.0002.0002.00026.000Maximum25405.00032080.00010.00020.00054.000Sum21354899612443511583877Count1001001001001003.3.CORRELATIONS BETWEEN VARIABLESNext we computed the correlation between the variables. Table 2: Correlation matrixSavingsIncomeFamilysizeEducationAgeSavings1Income0.5856081Family size-0.04631-0.093851Education0.4861520.507871-0.022231Age0.4296180.408807-0.2382741
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