Statistical Analysis of Young Professional Magazine Subscribers Report

This report presents a statistical analysis of survey data collected from subscribers of the Young Professional magazine. The analysis aims to understand the subscriber profile and identify the best articles to attract more investors. The data, obtained through a questionnaire survey, includes variables such as age, gender, income, investment value, and internet access. The report utilizes descriptive statistics, including counts, proportions, mean, median, and standard deviation, to summarize the data distribution. Confidence intervals are calculated to estimate the mean age and household income, as well as the proportions of subscribers with internet access and children. The findings suggest that the magazine is a suitable platform for online advertising, companies selling educational software, and computer games for children, and that technology and business-related articles would be of interest to the readers. The analysis concludes by highlighting the magazine's potential based on the subscriber demographics.

Running head: STATISTICS AND DATA ANALYSIS 1
Statistics and Data Analysis
Student Name
Professor’s Name
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Date

STATISTICS AND DATA ANALYSIS 2
Statistics and Data Analysis Report
Introduction
The purpose of the report is to provide an analysis of the data collected from random
survey of the Young professional magazine subscribers. The analysis will aid the company in
determining the best articles for the subscribers and to determine the subscriber profile which
will in turn be used by the magazine to attract more potential investors. Data is analyzed in with
the aid of excel statistical tool.
Description of Data and Data collection
The data obtained for analysis is primary data obtained from randomly sampling
subscribers through questionnaire survey. The data has a total of eight variables. The variables
age, investment value, transaction number and income of the household are continuous numeric
whereas the variables gender, real estate purchase, broadband and house children are categorical
(Shao, 2010).
Data Analysis
Descriptive Statistics
These statistics are used to explain the distribution of the data and are subdivided into
two main categories those of the categorical variables and those of the numeric variables. For the
categorical variables, the descriptive statistics used are count and proportion (Selvanathan &
Keller, 2017). The tables below summarize the descriptive statistics for categorical variables:

STATISTICS AND DATA ANALYSIS 3
Descriptive Statistics for categorical variables
Gender
Row Labels Count of Gender Proportion
Female 181 0.44
Male 229 0.56
Grand Total 410
Broad band Access
Row Labels Count of Broadband Access?Proportion
No 154 0.38
Yes 256 0.62
Grand Total 410
Real Estatate Purchase
Row Labels Count of Real Estate Purchases?Proportion
No 229 0.56
Yes 181 0.44
Grand Total 410
Have Children
Row Labels Count of Have Children? Proportion
No 191 0.47
Yes 219 0.53
Grand Total 410
From the descriptive statistics of the categorical variables, the proportion of female subscribers is
0.44 while the proportion of male subscribers is 0.65. The proportion of subscribes with
broadband access is 0.62 while those without is 0.38. The subscribers who prefer real estate
purchase is 0.44 while those who prefer not to purchase real estate is 0.56. 47% of the
subscribers have children while 53% have no children.
The descriptive statistics for the numeric variables are summarized by the table below:
Descriptive Statistics for numeric variable
Age Value of Investments ($) Number of Transactions Household Income ($)
Mean 30.11 Mean 28538.29 Mean 5.97 Mean 74459.51
Standard Error 0.20 Standard Error 780.84 Standard Error 0.15 Standard Error 1719.55
Median 30.00 Median 24800.00 Median 6.00 Median 66050.00
Mode 32.00 Mode 0.00 Mode 5.00 Mode 60300.00
Standard Deviation 4.02 Standard Deviation 15810.83 Standard Deviation 3.10 Standard Deviation 34818.21
Sample Variance 16.19 Sample Variance 249982368.72 Sample Variance 9.62 Sample Variance 1212307794.38
Kurtosis 0.02 Kurtosis 5.65 Kurtosis 2.46 Kurtosis 7.50
Skewness -0.03 Skewness 1.71 Skewness 1.21 Skewness 2.01
Range 23.00 Range 133400.00 Range 21.00 Range 306300.00
Minimum 19.00 Minimum 0.00 Minimum 0.00 Minimum 16200.00
Maximum 42.00 Maximum 133400.00 Maximum 21.00 Maximum 322500.00
Sum 12346.00 Sum 11700700.00 Sum 2449.00 Sum 30528400.00
Count 410.00 Count 410.00 Count 410.00 Count 410.00
The measures of central location are mean, median and mode whereas the measures of
spread are standard deviation and variance (Hinton, 2014). Where mean is greater than the
median and mode, the data is positively skewed indicating that most data points on the

STATISTICS AND DATA ANALYSIS 4
distribution are on the right side of the distribution. On the other where the mean is less than
median and mode, the data is negatively skewed indicating that most data points lie on the left
side of the distribution.
Confidence Intervals
Confidence interval for mean age and household income of the subscriber.
The confidence interval for the mean age and household income of the subscribers is
shown in the table below:
Age Household Income ($)
Mean 30.11 Mean 74459.51
Standard Error 0.20 Standard Error 1719.55
Median 30.00 Median 66050.00
Mode 32.00 Mode 60300.00
Standard Deviation 4.02 Standard Deviation 34818.21
Sample Variance 16.19 Sample Variance 1212307794.38
Kurtosis 0.02 Kurtosis 7.50
Skewness -0.03 Skewness 2.01
Range 23.00 Range 306300.00
Minimum 19.00 Minimum 16200.00
Maximum 42.00 Maximum 322500.00
Sum 12346.00 Sum 30528400.00
Count 410.00 Count 410.00
Confidence Level(95.0%) 0.39 Confidence Level(95.0%) 3380.26
Lower Limit 29.72 Lowe Limit 71079.26
Upper Limit 30.50 Upper Limit 77839.77
Interval 29.72≤x≤30.50 Interval 71079.26≤x≤77839.77
The 95% confidence interval for the mean age is between 29.72 and 30.50. This means that at
95% level of confidence; the actual average age of the magazine subscribers is between 29.72
and 30.50. On the other hand, the 95% confidence interval of house income is between $71079
and $77839.77. This means that, at 95% confidence level, the actual average house income of a
subscriber falls within the two values (Freund, 2014).
Confidence interval for the proportion of subscribers who have internet access and the
proportion of subscribers who have children.
The confidence interval for the proportion of the subscribes who have internet access at
home is shown is the table below:

STATISTICS AND DATA ANALYSIS 5
Confidence Interval for proportion with Internet Access
Proportion with access 0.62
Sample size 410
Confidence Level 0.95
Alpha value 0.05
Alpha/2 0.03
Z value 1.96
Standard error 0.02
Margin of Error 0.047
Lower Limit 0.573
Upper Limt 0.667
Confidence Interval 0.573≤p≤0.667
The confidence interval indicates that there is a 95% guarantee that the true proportion of
the subscribes with internet access is between 0.573 and 0.667 or alternatively, its between
57.3% and 66.7%.
The confidence interval for the proportion of individuals with children is shown below:
Confidence Interval for proportion with children
Proportion with children 0.53
Sample size 410
Confidence Level 0.95
Alpha value 0.05
Alpha/2 0.03
Z value 1.96
Standard error 0.02
Margin of Error 0.048
Lower Limit 0.482
Upper Limt 0.578
Confidence Interval 0.482≤p≤0.578
The confidence interval indicates that there is a 95% guarantee that the true proportion of
subscribers with children is between 0482 and 0.578.
Discussion
Whether Young Professionals is a good advertising outlet for online brokers
Yes, the Young Professionals magazine is a good advertising outlet for online brokers.
From the statistical analysis of the confidence interval, it is evident that the proportion of
subscribers who can access internet at home us between 57.3% and 66.7%, the proportion is

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above average and hence suitable for the online brokers to advertise their service to the
subscribers.
Whether the magazine is a good place to advertise for companies selling educational
software and computer games for young children.
Yes, the magazine would provide a better platform to advertise for companies selling
educational software and computer games for young children. From the confidence interval
analysis above, the proportion of subscribers with children is between 48.2% and 57.8%. The
proportion is large enough to all the magazine advice the software and the computer games with
the target audience being the children represented by the proportion.
Types of articles you believe would be of interest to readers of Young Professional.
The various types of articles that would interest the readers of the Young Professional are
those that would target the young population the magazine was developed. They include:
 Technology articles: Articles about current and emerging technologies tend to attract the
attention of young readers and therefore would be suitable for the magazine since its
intended for young readers.
 Business articles: Young reader are all always enthusiastic about business and investment
which would make articles of the same topic be suitable for the given population.
Conclusion
The purpose of the report was to present an analysis of data for the Young Professionals
magazine to aid in understanding the subscriber’s profile and determination of the best articles
for the magazine which would intern attract more investors. The analysis of data has been done

STATISTICS AND DATA ANALYSIS 7
on the basis of descriptive statistics and confidence interval. From the analysis the actual average
age of subscribers of the magazine is between 29.72 and 30.50 indicating a youth population.
The actual average of the house income of the subscribers is between $71079 and $77839.77.
The proportion of the individuals with internet access is between 57.3% and 66.7% and that of
subscribes with kids is 48.2% and 57.8%. The analysis above indicate that the magazine is
suitable for online advertisement, can advertise educational software’s’ and games for children
and that the kind of article that would interest the readers would either be business or technology
based.

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References
Freund, J. E. (2014). Modern elementary statistics (12th ed). Boston: Pearson.
Hinton, P. R. (2014). Statistics explained (3rd ed). London: Routledge, Taylor & Francis Group.
Selvanathan, E. A., & Keller, G. (2017). Business statistics abridged (7th ed). South Melbourne,
Victoria: Cengage Learning.
Shao, J. (2010). Mathematical statistics (2nd ed). New York: Springer.