The Case Analysis of Roxanne Quimby

Study of continuous variables

Sabin Adhikari

2017-04-25

Data Analysis and Business Intelligence

Mr Rabindra Silwal

Presidential Business School

Westcliff University

Abstract

This article provides a reports of the study of 3 continuous variables selected from excel97, which includes the 132 variables and 50 observations.  And then these three continuous variable are used to prepare the 3 contingency table using 2 variables on each table. The main aim of preparing the contingency table after selecting these three variables is to study the level of correlation between the three variables.  Finally, the result are presented at the end with some relations between the variables.

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Study of  continuous variables

We simple use a tool called Contingency table, when there is requirement of investigation of data which comprises more than one variable. The contingency tables are also known as cross tabulation (cross tab). Matrix or grid form is used to determine the contingency table. Usually, the variable’s frequencies are established in this type of table. (Colignatus, 2007)

A variable is a value that can alter or change, dependent on situations or on evidence passed to the program. In simple words variable are a quantity that have changing value. A quantity having a changing value can be termed as a variable. A variable that comprises infinite digit of possible values is known as a continuous variable. The continuous variable differs from discrete variable that constraints of having only particular number of values. For instance: discrete variables are normally the numbers (5, 6, 7…). In contrast, the continuous variables can be both normal numbers and numbers in decimals too like (5, 6, 7…) and (5.1, 6.2, 5.3, 7.4…) (Lucidi, Piccialli & Sciandrone, 2005).

        I have selected the following three continuous variables as per the question requirement and I have find out the correlation between the three variables using the high, low and medium techniques i.e., using contingency table.

 Economy (Unemployed male) 1996 percent unemployment of males in civilian labor force

Education (Dropout) 1995 public high school dropout rate

Education (Graduate) 1995 public high school graduation rate

                 Contingency table (Dropout and Unemployed Male)

The above contingency tables shows the low, medium and high value in respect to Dropout rate in 1995 public high school. Analyzing the state97.xls database, it is clear that the provided contingency table shows that the Dropout has high value of 44.9 in South Carolina. Similarly, the average value of dropout is 26.9 in both Colorado and Arkansas. This value is also known as median value. On the other hand lowest value of Dropout is 10.6, which is found in Vermont.

On the other, in 1996, the unemployment rate of all male has lowest value of 2.7 is found in the state Nebraska. In contrast, highest unemployment rate is observed in Alaska and the value is 9.1. However, the median value of unemployment is 5.1, which is found in three states namely, Wyoming, Idaho, Michigan.

Similarly, with the increase in 1995 dropout rate the 1996 unemployment among the male population seems to increase. This shows the positive relation stating that more drop out results in more unemployed males. At median dropout rate of 26.9, the percentage of unemployment male is 5.4 at Arkansas. Similarly, at high dropout rate of 44.9, the percentage of unemployed male is 5.8 at S Carolina. And at the lowest dropout rate of 10.6, we see the percentage of unemployed male is 4.5 at Vermont. Hence, it is clear that due to lack of education the dropout male peoples are not employed (Cherry & Wang, 2015).

    Contingency table (UnemMale and graduate rate)

As it can be understood from the above contingency table that the variable (UnemMale) has the average value (5.1) calculated from several observations of the given 50 states which is also the median value. Analyzing 132 variables and 50 observations provided in the State97.xls database, it is found that the states Idaho, Michigan and Wyoming come under the average unemployment rate value which is (5.1). Furthermore, the unemployment rate is found higher in state Alaska (9.1) followed by the lower in state Nebraska with the value (2.7).

Likewise, in case of variable (Graduate rate) 1995 in Public high school. The largest rate of students who graduated is 89.4 in Vermont. Likewise, medium value for graduating students was 73.1 in Colorado and Arkansas. Similarly, the low graduation rate is found in South Carolina with the value of 55.1.

Analyzing the above data at the median graduate rate at 73.1, the percentage of unemployed male is 5.4 at Arkansas. On the other, at the high rate of graduate (89.4) the percentage of unemployed male is 4.5 at Vermont. At low graduate rate of 55.1 the percentage of unemployed male is 5.8 at South Carolina. Analyzing only these variables we see the negative relation as one increases other decreases. Hence, it can be inferred that higher the graduation rate lower the unemployed male. It means graduated male can find the work than that of those who are not graduated.