Technology Tools

Posted: August 27th, 2021

M1D1: Technology Tools

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M1D1: Technology Tools

Technology tools are critical in easing statistical analysis. They enhance analytical accuracy, speed, and efficiency. In this regard, the paper discusses the pros and cons of three essential statistical tools. They include StatCrunch, Excel, and the TI 83/84 graphing calculator.

StatCrunch is accessible through MyStatlab. This statistical software was created to solve modern statistical packages such as SPlus, Minitab, and others(Bruce, 2015). It is targets learners who are not proficient with delivery and use languages required in other complex statistical software(EVANS, 2019). However, the tool does not allow users to print or copy the work unless you are using a premium version. Thus, these inabilities limit users.

Regarding excel, it has the best functions for organizing large data amounts as facilitated through its logical charts and spreadsheets. Hence, this makes it easier to analyze. However, the package requires time to learn, and not anyone can handle it. Lastly, the R-Programming tool is readily available from open sources(EVANS, 2019). Besides, the software offers the best to transform mixed-up data into structured(EVANS, 2019). Equally, the software provides high quality plotting and graphing, enhanced through its popular libraries such as plotly and ggplot.However, it is not without challenges(Bruce, 2015). The R software shares a weak origin because of the old programming language called “S”; hence it is incompatible with various dynamic programming languages.

 Among the three essential statistical software, Excel happens to be the best. Hence, my leaning is towards this tool. The reason is that I am proficient with its use, which makes it easier to maneuver. However, before making the final decision, I need information on the type of data. Excel will work best with quantitative rather than qualitative. Nevertheless, I do not need help to get up with speed since I am well equipped with Excel skills. Besides, I have some open source resources that can be helpful. Therefore, this will enhance my performance with the tool.

References

Bruce, P. (2015). Introductory statistics and analytics: a resampling perspective. Hoboken, New Jersey: Wiley.

EVANS, J. (2019). Business analytics plus mylab statistics with Pearson etext — access card package. Place of publication not identified: PRENTICE HALL.