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Business Statistics Learning : Contemporary Decision Making

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Question:

Discuss about the Business Statistics Learning for Contemporary Decision Making.
 
 

Answer:

Introduction:

Statistics is defined as a branch of science dealing with data collection, data analysis, data tabulation, and data presentation. The two major types of statistics are the descriptive and inferential statistics (Berenson et al., 2012). Descriptive statistics is concerned with measures of central tendency whereas inferential statistics encompasses on estimation and hypothesis testing.

This assignment summarizes topics on data types and their scale of measurement with relevance to the essay. We analyse the use of descriptive or inferential statistics in to present a situation. Further we investigate the use of probability in presenting a practical world problem.

The essay selected for the present assignment is “Building Approvals: Sydney (NSW) housing activity still “smoking” in January.” In the assignment we study the building approvals in states. The frequency of approvals of dwelling in the private sector from 2009 to 2017 has been studied. Both multi-unit and single unit housings approved have been studied. We further study the frequency of residential buildings approved in different states of Australia with emphasis on NSW, Vic, QLD, WA, SA and ROA. Moreover, the number of buildings approved in the non-residential sector is also studied.

The source of the present data is the building approval committee of different states. Quantitative data is used for the study.  Data is measured in interval scale. 

The data in the essay is presented in various forms.

To evaluate the total approvals in residential sector ratio scale is used (Keller, 2015). With the use of ratio scale comparison of total approvals in 2015 to 2017 is done. To compare the approvals in states percentage scale has been used.

Three graphs are presented in the essay. All the three graphs are time series line graphs. Different time lines have been used in the graphs. The time scale is on x-axis. The frequency scale is in y-axis.

 

Measures of location are used in statistics to find the central tendency of the data. The three measures of central location are mean, median and mode (Gorini, 2012). Mean is given as the ratio of the sum of the values in a sample to the size of the sample. Median can be defined as the mid-point of the ordered data sample (Brase, 2015). Mode is the most frequently occurring data in the sample. In the present essay Central location has not been used to study the building approval rate.

The distribution of the data in a sample if used measures variation in a sample. Range and quartiles are used to measure variations in a sample (Newbol, 2013). Range is the difference between the maximum value and minimum value in the sample. In an ordered data set quartile divides the data set into four equal halves. In the present essay on approvals of buildings measures of variation is not used.  

Descriptive statistics is used in the essay to summarise the data. Descriptive statistics is the use of measure of central tendency and variability to study a variable (Black, 2013) . Different measures of central tendency are mean, median and mode. The central tendency measures the central location of a dataset. However in the essay central tendency is not used. The sum of the total number of approvals in 2015 and 2016 is used for evaluation with the expected approvals in 2017.   In statistics data is collected, evaluated and analysed and then presented in a form by which the common person can understand. Statistics is used to analyse situations in every sphere of life – weather, disease, business, politics, quality testing etc. In a business environment statistics can be used to analyse data and make decisions based on the analysis.   

In the present essay longitudinal building data has been collected. The data of the buildings is presented in both numerical as well as graphical from. The numerical longitudinal data has been grouped into three heads – residential and non-residential buildings and buildings in a state. The residential data is further divided into houses and multi-unit houses. Building approvals is studied with the help of frequency and ratio analysis. The building approvals for each state are used to compare the growth (percentage) in the states. In the non-residential sector the building approved in different sectors for non-residential use is compared. The numerical data has also been presented in graphical from.

The numbers used to compare the data can be beneficial for key policy makers. The analysis of the numbers shows the trend in growth (or decline) in the building industry. The study of the numbers can be used by policy makers to make decisions. The present data can be used to understand the differences in supply and demand of buildings. Thus governments can make provisions for filling the gap.  

 

References

Berenson, M., Levine, D., Szabat, K., O'Brien, M., Jayne, N., & Watson, J. (2012). Basic business statistics: : Concepts And Applications (3rd ed.). Pearson Higher Education.

Black, K. (2013). Business Statistics: For Contemporary Decision Making (8th edn). Wiley Global Education 2013

Brase, C. H. (2015). Understanding basic statistics. Cengage Learning.

Gorini, C. A. (2012). Master Math. Boston: Cengage Learning.

Keller, G. (2015). Statistics For Management And Economics (10th edn). Cengage Learning

Newbol, P. C. (2013). Statistics for business and economics. Boston: Pearson.

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