# Ryan Deluna. Independent Project. 1.Frequency Distribution

973 WordsMar 30, 20174 Pages

Ryan DeLuna
Independent Project
1. Frequency distribution of a variable and bar graph of the same variable
A frequency distribution table is used for arranging data values and counting the number of time each value appears in a dataset. They can be used for both qualitative and quantitative variables. For this data pool I decided to use the subjects’ marital status because it is a qualitative, nominal level variable. (Polit, 23)
Frequency table results for racethn:
Count = 972 racethn Frequency Relative Frequency Percent of Total
Black, not Hispanic 795 0.81790123 81.790123
Hispanic 123 0.12654321 12.654321
White, not Hispanic 54 0.055555556 5.5555556
The table above is a frequency table that shows the relative frequency and the percent*…show more content…* The summary includes variance, mean, median, mode and standard deviation. As shown in the histogram majority of people in the data pool have a height of 62-68 inches. This is a symmetrical distribution seeing how close the mean and median are to each other.
3. Cross tabulation of two variables
A cross tabulation is a two-dimensional frequency distribution of two nominal or ordinal variables that records the frequency of respondents that have the specific characteristics. These tables provide a wealth of information about the relationship between the variables. For an example I chose to use poverty levels and smoking to show how a contingency table can illustrate a frequency distribution. Poverty level is a nominal variable that will be the independent variable and the dependent variable will be smoking. The end table is a chi-square test and it is used to determine if the variables are unrelated.
Contingency table results:
Rows: smoker
Columns: poverty
Cell format
Count
(Row percent)
(Column percent)
(Percent of total)
(Expected count)
(Contributions to Chi-Square)
Above poverty Below poverty Total
No
Count
(Row percent)
(Column percent)
(Percent of total)
(Expected count)
(Contributions to Chi-Square) 127
(25.87%)
(58.26%)
(13.13%)
(110.69)
(2.4) 364
(74.13%)
(48.6%)
(37.64%)
(380.31)
(0.7) 491
(100%)
(50.78%)
(50.78%)
Yes
Count
(Row percent)
(Column percent)
(Percent of