Analysis Of Gender Variation In Tobacco Consumption Among Youths

Stating Clear Questions and Collecting Data

being an employee of the human resources department in a large biomedical company, it is of the main interest to test the variation in the use of tobacco across gender. smoking has become a signature of status to both males and females. it is still expected that the percentage female smokers are less than that of male smokers (krueger, krueger & koot, 2015). thus, in support of this claim, this research has been conducted. to conduct this research, the following null and alternative hypothesis has been framed.

null hypothesis (h₀): there are no significant differences in the percentage of male and female youths smoking frequently.

alternative hypothesis (h_a): there are significant differences in the percentage of male and female youths smoking frequently.

proposed data collection

the data collected was collected from a secondary data source. the data from catalog.data.gov (2018) on the tobacco consumption by the youths has been collected. a lot of variables and values were present in the data selected. from the whole dataset, the necessary rows and columns were extracted. as the aim of this research is to test gender variation in the use of tobacco, the values of male and female individuals who smoke frequently over the country has been selected. from the whole data, 24 data points have been obtained which contained information of frequent male and female smokers over the united states in the year 2015.

actual data collection

the data collection process was extremely simple and was conducted very easily. the extracted dataset that is used for the analysis is given in the appendix section along with the variance statistics of the data.

to conduct the analysis, the first thing that has been computed are some basic descriptive statistics measures such as the mean, the median, the mode, the standard deviations. the measures obtained as a result of the analysis are given in the following table 1. from the table, it can be seen that the average percentage of male frequent tobacco users is 2.175 whereas the average percentage of female frequent tobacco users is 1.47. the study has been conducted on youths. thus, from here, it can be said that quite a large percentage of the youths are tobacco users, irrespective of males and females as the percentage of smokers reflect the percentage of the total population of the united states. the whole population is not comprised of the youths. there are people of all age groups. from the table, it can also be seen that the sample variance in males is 3.61 and that in females is 2.36. this indicates that there is quite a large variation in the consumption in males and a comparatively smaller variation among the females in terms of frequent smokers. thus, it can be said from here that the consistency of the frequent female smokers is higher than that of frequent male smokers.

Formulating Clear Hypotheses

table 1: descriptive measures for the male and female frequent smokers

male		female
mean	2.175	mean	1.470833
standard error	0.387591	standard error	0.313725
median	1.75	median	1.1
mode	0.2	mode	0.1
standard deviation	1.898798	standard deviation	1.536931
sample variance	3.605435	sample variance	2.362156
kurtosis	-0.78685	kurtosis	-0.1966
skewness	0.56321	skewness	0.92625
range	6.3	range	5.2
minimum	0	minimum	0
maximum	6.3	maximum	5.2
sum	52.2	sum	35.3
count	24	count	24

source: as created by author

apart from the descriptive analysis conducted above, there is another important tool that can be used to draw a conclusion about the data. this is known as the variability test. the mean and the variance discussed in the part earlier is affected by the presence of any extreme values. thus, a more standardized measure has been computed to test the variability of the data. this is known as the variability test. from the mean scores, it was not possible to obtain the actual clear picture of the percentage of youth that smoke in different states of the country. thus, it was not possible to understand whether the null hypothesis proposed earlier will be accepted or rejected. thus, from the figure given below, figure 1 shows that the data is almost normal. it can also be seen that value of skewness obtained from table 1 is close to zero. thus, the data can be considered as symmetric. similarly, from figure 2, it can also be seen that the data is symmetrically distributed.

The final test that has been conducted here is the t-test. this test has been conducted as this is the most appropriate test that can be conducted in order to test the difference of the means between two factors. here, the main interest was to test the difference in the percentage of frequent smokers across gender. from the results of the analysis as shown in table 2, it can be seen that the p value obtained is 0.165, which is more than the 95 percent level of significance. thus, from here, it can be said that that the null hypothesis is accepted. there are no significant differences in the average number of male and female smokers.

table 2: two-sample t test assuming equal variances

	male	female
mean	2.175	1.470833
variance	3.605435	2.362156
observations	24	24
pooled variance	2.983795
hypothesized mean difference	0
df	46
t stat	1.412152
p(t<=t) one-tail	0.082317
t critical one-tail	1.67866
p(t<=t) two-tail	0.164635
t critical two-tail	2.012896

source: as created by author

Conclusion

the results of the test that has been conducted has shown no support the hypothesis stated above. the male and the female youths do not have any significant difference in terms of smoking. both the genders have a significantly equal percentage of the whole population of frequent smokers.

however, this is the result of an extremely basic analysis. further analysis can be conducted based on these results. the original dataset consisted of data on the tobacco consumption from 1999 to 2015. thus, the increase or decrease in the percentage of females and male smokers can also be tested.

References

krueger, h., krueger, j., & koot, j. (2015). variation across canada in the economic burden attributable to excess weight, tobacco smoking and physical inactivity. can j public health, 106(4), e171-7.

prevention, c., & support, o. (2018). youth tobacco survey (yts) data – data.gov. catalog.data.gov. retrieved 17 march 2018, from https://catalog.data.gov/dataset/youth-tobacco-survey-yts-data