Introduction to Quantitative Analysis: Descriptive Analysis

Age (Q1) Category Data 

Using IBM-SPSS, the following summary is produced.

Statistics
Q1. Age
N	Valid	10250
	Missing	69
Mean		37.01
Median		34.00
Mode		30
Std. Deviation		14.536
Skewness		.888
Std. Error of Skewness		.024
Kurtosis		.260
Std. Error of Kurtosis		.048
Range		81
Minimum		18
Maximum		99
Sum		379321

For your continuous variable: 

1. Report the mean, median, and mode 

For the data, the Mean is 37.01; Median is 34.00, and Mode 30 indicates the common age.

2. What might be the better measure for central tendency? (i.e., mean, median, or mode) and why? 

This data skewed (i.e., skewness statistic=0.888); hence, using the median would be vital as the best measure. The reason lies in the effect of outliers, i.e., extreme values lying at the variable´s either end (Frankfort-Nachmias, Leon-Guerrero & Davis, 2020).). Since mode and mean are very much affected by existing outliers in the dataset, they become less efficient for the age dataset. Hence, in this case, since outliers do not here impact the median, it will be the best measure for the data scores.

3. Report the standard deviation 

Standard deviation = 14.536

4. How variable are the data? 

Standard deviation forms an essential measure of variability, depicting how data points are spread relative to the obtained mean (Frankfort-Nachmias, Leon-Guerrero & Davis, 2020). Hence, with a Standard deviation of 14.536, it shows the data points for age are spread out, away from the mean. This can be demonstrated with this histogram;

5. How would you describe this data? 

The Age data is non-symmetrical, as it is positively skewed (skewness statistic=0.888), with more data points lying on the right. Also, with an SD= 14.536, there are much data points spread.

6. What sort of research question would this variable help answer that might inform social change? 

Two research questions encompassing this Age variable can help inform social change, i.e.,

Does one´s age contribute to being susceptible to osteoporosis (bone disease)?

Is there an association across one´s age and employability in the technology industry?

Education Category Data 

Using IBM-SPSS, the following summary is produced for frequency statistics.

Statistics
Education Category
N	Valid	10301
	Missing	18
Mean		1.40
Median		1.00
Mode		2
Std. Deviation		.949
Skewness		.007
Std. Error of Skewness		.024
Kurtosis		-.941
Std. Error of Kurtosis		.048
Range		4
Minimum		-1
Maximum		3
Sum		14409

Post the following information for your categorical variable: 

1. A frequency distribution. 

Education Category
		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	-1	4	.0	.0	.0
	No formal education	2105	20.4	20.4	20.5
	Primary	3261	31.6	31.7	52.1
	Secondary	3641	35.3	35.3	87.5
	Post-secondary	1290	12.5	12.5	100.0
	Total	10301	99.8	100.0
Missing	Don't know	18	.2
Total		10319	100.0

2. An appropriate measure of variation. 

For the categorical data, in this case, education, there seems no appropriate measure, based on what Wagner (2020) shows, can offer a proper variation measure. The best tool is comparing one group, to another, for example, primary vs. secondary, or in other cases, secondary vs. post-secondary.

3. How variable are the data? 

The data is symmetrical, i.e., normally distributed across the varied education categories. A histogram can help show data distribution (Wagner, 2020), and for education data, this can be shown by the histogram depiction below;

4. How would you describe this data? 

There is a normal distribution for the different educational groups, i.e., based on skewness statistic=0.007, which is almost zero; this helps show that the data is bell-shaped.

5. What sort of research question would this variable help answer that might inform social change? 

Two research questions entailing education can help inform social change, i.e.,

1. Does one´s education status affect their future income levels and wealth accumulation?

2. Does an individual´s educational level impact on their employability?

References

Frankfort-Nachmias, C., Leon-Guerrero, A., & Davis, G. (2020). Social statistics for a diverse society (9th ed.). Thousand Oaks, CA: Sage Publications.

Wagner, III, W. E. (2020). Using IBM® SPSS® statistics for research methods and social science statistics (7th ed.). Thousand Oaks, CA: Sage Publications.