Data Summary and Discussion

The data presented shows the amount charged on credit cards by households of a given size and income. This data shows that while the amount spent by households varies depending on the size and income, the combination of both might also have an important bearing on the amount of that household’s debt. The debt range for the entire data set of 50 households is $1,864 to $5,678 per year, while the incomes in the set range from $21,000 to $67,000 per year. The households’ sizes in this data set range from one (1) to seven (7). When each variable is taken singly, one finds that each does to a significant extend predict the amount of debt that the household carries. What is specifically shown in this data is that households tend to have a higher amount of debt depending on the number of persons who live in the house, as it largest households generally carry a debt amount that lies on the higher end of the spectrum. For example, the average debt for the three seven-person households lies at $4,911, which is only about seven hundred dollars below the highest debt amount of $5,678. The data also shows that the average debt for the five one-person households is approximately $2,781.

However, what the data also shows is that even though debt rises as the household size rises, it does so at a decreasing rate. The fact that the average debt for one-person households is significantly higher than the lower end of the range demonstrates that the low end might represent an extraneous amount, and indeed it does. This is the debt carried by a two-person household. A better comparison of the one-person household average debt could be made with the calculated debt per head for the entire data set. The total number of persons in all households is 171, and the total debt for all households is $198,203.

The average debt per capita for this group of persons is about $1,159. This, compared with the average debt for the one-person households, shows that the debt for the one-person households does represent a disproportionately high size of twice as much as the overall per capita debt. This might be explained by the fact that the fixed costs for households generally remain relatively the same regardless of how many persons may live in the house. Other factors that bear on this are extraneous, such as the spending patterns and financial awareness of the persons in each household. However, another major factor to consider in predicting household debt is the annual income of the persons within each house.

Order custom essay Data Summary and Discussion with free plagiarism report

450+ experts on 30 subjects Starting from 3 hours delivery

Get Essay Help

Which is a Better Predictor: household size or income?

However, further analysis shows that even household, by itself, does not predict the amount of debt very well. In fact, the data points toward the fact that household size predicts the annual credit card charges better than household income. Looking back at the previous example, one sees a household that earns $26,000 producing debt comparable to most of the higher-end earners.

Part of this debt size has to be attributed to the fact that the household earning such a small income in comparison to other household is faced with the challenge of supporting seven persons. Another household earning $23,000 supports six persons and shows credit card charges of $4,127 per year. Other households of comparable earnings ($21,000 and $27,000) show smaller credit card charges of $2,448 and $2,477 respectively, and this can be attributed to their smaller household sizes.

Combination of Household Size and Earnings

The income range for the data set has already been stated as $21,000 to $67,000. The total income for this group is $2,174,000 and the average income is $43,480. The average debt for each household is $3,964 which falls approximately in the middle of the $1,864 to $5,678 range. However, what one notices is that though the average debt for the three 7-person households is shown to be $4,911, the highest debt in that segment goes to the household with the highest income.

Therefore, the $5,301 debt goes to the household that earns $55,000 per year, while the lowest debt of $4,603 goes to the household that earns only $26,000 per year. This demonstrates that the combination of household size and household income is an overall better predictor of credit card charges that any of those variables alone. According to this, a household made up of three persons and earning $40,000 should show a credit card charge within the median range of about $3,800 - $4,100. This would be expected to be comparable to any other household of three persons, yet slightly below those households of three that have higher earnings.

Other Data Necessary to Make Accurate Predictions

Other information concerning these households’ loans, mortgages, and neighbourhood locations would also be requested of the client. According to the discussion above, though, it would appear that despite the fact that household size predicts the annual credit card charges better than household income, other factors also affect the size of credit card debt. What one notes is that most of the low-earning households do still show a disproportionately higher amount of debt than their counterparts of high-earning households with similar household sizes. Households that, for example earn twice as much as another do not generally show twice as much debt in this data set.

Neither is this so for households that have twice as many persons. One contributor to this is the existence of fixed costs, as mentioned above. However, this does not account for all the discrepancies. Therefore, other factors that might contribute to credit card charges include the amount of previous debt (such as university tuition loans, mortgages, etc) that each household has incurred. They may also include the household’s attitude toward its finances and toward debt in general. Other factors involve the cost of living within the geographical area of the particular household and the general lifestyle to which the household is accustomed.

Work Cited

Professor’s Name. “Data Sheet.” Name of Class. City: University, 2007.

Don't let plagiarism ruin your grade

Run a free check or have your essay done for you

Check my essay Hire Writer