Interpreting Data: Stat Meth, Market Strategies & Business Decisions - Report Sample

Introduction

There are so many statistical methods that can be used in interpreting the data. Analysis of the operation of data to make decisions about the information it is portraying in either pictorial representation to give clear information on the data. Furthermore, there are current strategies in the market that helps the business to win the market and get clear, futuristic speculation basing on the data. Moreover, the recommendation of the action business decision needs to relay on the information of the data. In interpreting and analyzing data. The first-hand information on the understanding of how data support analytics on decision making hence and values to an organization.

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Scope and Descriptive Statistics

The statistical description of the restaurant specialization on the foods that the majority of the people love meals. In the choice of where to establish growth and diversification of other new branches. The age of 25-45 is the target population since they are the primary customer of the organizations. The offices are to be established in the 3-mile radius from the first one. The keen consideration of suitable demographic conditions where their customers can access their services in the shortest time possible and with ease (Coyne & Wyrwich, 2015). The current database elaborates that the majority of the consumers of the restaurant foods are the middle age between 25-45. However, some ask for noodles-based dishes in plenty, soups, and salads as their favorite. The variable that needs to be Cleary scrutinize in the analysis is sales growth annually, the area covered in square feet. Bachelor’s degree by the qualification, the age bracket of the workers.

Descriptive Statistics Findings

The descriptive summary of the information of the data in statistics are in considerably on the data that is in the information about the variables (Coyne & Wyrwich, 2015). The uniqueness of the variables is important in the information.

Analysis

The analysis of the statistics is the information of the data being represented in the clear elaborative graphs and charts to give allow the information to be informative about the data in the discerption of the data (Li et al., 2019). More generally, the analysis can be done on the graphs, the charts example being the box plot, histography, the diversified information, and the pictorial analysis.

Effective Expansion Criteria

Based on the finding, the asses of the expansion are to target the youth and the growth of business sales. The employment of the bachelor’s degree employees gives the restaurant the capability of having skillful and qualified employees. The vendors of the restaurant should be employees too to make more sales. The targeted consumers need to in market.

Loyalty Card Correlation

The loyalty card has a positive correlation with the sales growth in the organization, ensuring the employees and the companies have an effect on growth (Zhou et al., 2010). The marketing strategy needs to ensure online marketing and free deliveries to online orders; furthermore, the employees need to be well conversant with the internet. Additionally, qualified employees need to be a chef in the restaurant (Ristow & D’Amato, 2017). The posters and the Barnes of adverse on the streets need to be raised by the organization.

Positive Target to Specific Demographic

The young people are the major customers to the establishment. E-commerce is of great advantage to them in the organization (Ostrom et al., 2019). The restaurant should give priority to the middle age being large in numbers and love with the restaurant meals. Nonetheless, the data to clearly understand the information on the restaurant progress need to have a survey on the collecting of the data using the census integrated information system.

Information Should Be Collected to Track and Evaluation

The information on the variables that are sensitive on the decision making should be clearly understand to speculate the future. The sales information to be tracked keenly. The information about the number of employees. The service information from the customers. The information for the customers. The population information on the age bracket of the majority of the customer. The occupation of the target customers demographically.

Conclusion

In any statistical report, the scope of descriptive statistics having the objectives of the news, clearly elaborated in the statistical information. The nature of the current database is necessary for the report analysis. The variables for the decision making are the dependent and the data collected that help tracks the prediction and give the decision making of the organization. Furthermore, the pictorial representation of the3 analysis sector, giving the box plot the scatter plot and other statistician graphs, help present the information. Additionally, statistically, after analysis of the data recommendation is based on the analysis and the variable difference dependent and independent variable. Nonetheless, the implementation of the information is helpful for the knowledge of the analysis. The decision of the futuristic information.

References

Coyne, K. S., & Wyrwich, K. W. (2015). ISPOR task force for clinical outcomes assessment: Clinical outcome assessments: Conceptual Foundation—Report of the ISPOR clinical outcomes assessment – Emerging good practices for outcomes research task force. Value in Health, 18(6), 739-740.
https://doi.org/10.1016/j.jval.2015.09.2863

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

Ostrom, Q. T., Cioffi, G., Gittleman, H., Patil, N., Waite, K., Kruchko, C., & Barnholtz-Sloan, J. S. (2019). undefined. Neuro-Oncology, 21(Supplement_5), v1-v100.
https://doi.org/10.1093/neuonc/noz150

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

Zhou, Y., Fleischmann, K. R., & Wallace, W. A. (2010). Automatic text analysis of values in the Enron email dataset: Clustering a social network using the value patterns of actors. 2010 43rd Hawaii International Conference on System Sciences.
https://doi.org/10.1109/hicss.2010.77