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

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