Paper Sample on Statistical Analysis and Data Interpretation

Introduction

Statistical analysis is a paramount model in the recommendation of the companies or business welfare. The record of data, the step by step manipulation, makes the information more useful in futuristic decision making. The information generated from the statistical analysis is a certificatory need to have the data presented. Generally, the statistical analysis component of data analytics presentation is essential. In the context of business intelligence, analysis of statistic involves scrutinizing and collection of daily data sample within a specific set of items which can be drawn for the conclusion. The example in the statistical representative selection drawn for the total population of the business running.

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Interpreting Data

In every statistical data collection, there is a need to understand the data sample. The data sample can be manipulated for interpretation in different ways. The variety of analytical tools in the statistics is essential in the data interpretation of useful information. The data can be interpreted with standard deviation, the mean, correlation, and also the regression analysis for clear understanding (Li et al., 2019). With the data collection, the survey samples and the experimental design is essential to understand the data. The variables in section need to have to be elaborated in the statistical analysis.

Annual Sales

The annual sales in making the product of sales/sqFt and the sqFT. It gives the yearly sales to have a maximum of 1652437.4; it quite the booming season that the organization restaurant is making where the majority were the middle age (Ristow & D’Amato, 2017). The square feet are 2354 being the increased area of coverage. However, the annual sales average of 1059381.314 for the 74. It gives the mean speculation to get the information in the sales and the yearly information that helps the restaurant on making the future dates of the business running.

Mean

The mean of arithmetic terms is the sum of all terms divided by some conditions, in the string. Mean computation always has the direction to the median the ode and the range of list. The mean for the square feet, sales/person, sales growth percentage, loyalty card, annual sales per square feet, median income, median age, and the bachelor’s degree are the following respectively 2580.472973, 7.044054054, 7.414054054, 2.026486486, 420.3054054, 62807.7027, 35.20135135, and 26.31081081.

Standard Deviation

Statistically, it is the quantity of expressing by how many members of the group differ from the mean value for the group. The deviation from the mean is used in ensuring that the information is not an outlier and can be used in decision making (Ristow & D’Amato, 2017). The following are the standard deviations for the square feet, sales/person, sales growth percentage, loyalty card, annual sales per square feet, median income, median age, and the bachelor’s degree are the following respectively 374.9190314, 0.2972611, 6.624730322, 0.552370812, 137.2395233, 17904.27295, 3.654552171 and 7.004745311.

Number Summaries

The five-number summaries are the essential statistical information used in the recommendation of the data. The mean, the median, the maxima, and the minimum interquartile range. The five-number summary help statisticians in projecting the information about the data.

It is essential that the statistical analysis of any presented the statistical information on the five-number summary is elaborated.

Interquartile Range

The interquartile range is the average of the upper and the lower section taking the mean to be the average. The upper limit is the top quartile, and the lower is, the lower quartile. The statistical software like excel gives clear information of the upper and lower quartile.

Box-Plot for the “Annual Sales” Variable

The box plot is the pictorial representation having the median the upper and lower quartiles. It helps in presenting some of the 5 number summaries in the graphic image.

Histogram Of “Sales/Sqft” Variable

The histogram shows the distribution of the information that is surrounded by the variables. The variables take into consideration of data considering payment of variable that are to measure their relation in

Measurer of Central Tendency

The measure of central tendency gives the elaborative information about the data being analyses. The central tendency provides elaborative information. The statistical represents the center point or the value of the dataset. The three most common measure of central tendency is the mean the median and mode.

References

Li, T., Fan, H., García, J., & Corchado, J. M. (2019). Second-order statistics analysis and comparison between arithmetic and average geometric fusion: Application to multi-sensor target tracking. Information Fusion, 51, 233-243. https://doi.org/10.1016/j.inffus.2019.02.009

Ristow, P. G., & D’Amato, M. E. (2017). Forensic statistics analysis toolbox (FORSTAT): A streamlined workflow for forensic statistics. Forensic Science International: Genetics Supplement Series, 6, e52-e54. https://doi.org/10.1016/j.fsigss.2017.09.006