Country Data File
Variable 3
Urban
Statistical Data Analysis
Note: This research was conducted using SPSS program for Descriptive Statistics
Introduction
The research is based on a sample of 122 valid scores and has no missing data among them. The purpose of this paper is to organize the data about the percentage of people living in urban areas in different countries and to make observations about the country development relating to this percentage.
Table 1: Main information Table 2: Grouped data frequency
Statistics | |||||
Percent urban | |||||
N | Valid | 122 | |||
Missing | 0 | ||||
Mean (μ) | 48,78 | ||||
Median | 48,00 | ||||
Mode | 25a | ||||
Std. Deviation ([pic 1] | 24,625 | ||||
Variance | 606,383 | ||||
Range | 95 | ||||
Percentiles | 25 | 27,75 | |||
50 | 48,00 | ||||
75 | 70,00 | ||||
a. Multiple modes exist. The smallest value is shown | |||||
Percent urban (Binned) | |||||
Frequency | Percent | Valid Percent | Cumulative Percent | ||
Valid | 90+ | 5 | 4,1 | 4,1 | 100,0 |
80 - 89 | 11 | 9,0 | 9,0 | 95,9 | |
70 - 79 | 15 | 12,3 | 12,3 | 86,9 | |
60 - 69 | 15 | 12,3 | 12,3 | 74,6 | |
50 - 59 | 13 | 10,7 | 10,7 | 62,3 | |
40 - 49 | 13 | 10,7 | 10,7 | 51,6 | |
30 - 39 | 16 | 13,1 | 13,1 | 41,0 | |
20 - 29 | 20 | 16,4 | 16,4 | 27,9 | |
10 - 19 | 10 | 8,2 | 8,2 | 11,5 | |
0 - 9 | 4 | 3,3 | 3,3 | 3,3 | |
Total | 122 | 100,0 | 100,0 |
Evaluation
The central tendency is used to find the single score that is most typical or most representative of the entire group and is measured by the mean, the median and the mode. The sample mean has a value of 48.78, which is slightly higher than the median with a value of 48.00. Although a distribution will have only one mean and only one median, it is possible to have more than one mode. In this case, the minor mode (25.00) is found. The range describes how spread out the scores are, but is highly affected by the extreme scores, because it is measured by subtracting the lower real limit of the smallest from the upper real limit of the largest. To avoid the influence of the extreme scores, it is common to measure the interquartile range by finding the 50th percentile (or by subtracting first quartile from the third). Thus, using SPSS program, the real limits of the maximum and minimum X values were not taken into account, so the range is 95 instead of 96 (URL - LRL: 100.5-4.5=96). Standard deviation and variance are most commonly used measures of variability. It is common that each score can be described in terms of its deviation or distance from the mean. The variance is the mean of the squared deviations and the standard deviation is found by calculating the square root of variance (. [pic 2]