My Professor Emailed Me About The Data Analysis Project ✓ Solved

My Professor Emailed Me About The Data Analysis Project Say

My professor emailed me about the DATA ANALYSIS PROJECT saying that I need to start by reducing the amount of data from the original spreadsheets and putting that into a new table in Excel. This way, I won’t show participants' names and it will be easier for readers to interpret the charts and graphs. You will need to analyze the data from the ML2 spreadsheet based on your evaluation questions.

Start with a simple table in Excel. We are looking at participants’ reading and math scores pre and post program. Once you have your table in Excel, you can select it, then click on “Insert,” “Charts” and select the kind of chart or graph you want to use. Once you have created the chart, you can right click on the data inside the chart to add labels and other specifics inside the chart.

Paper For Above Instructions

The purpose of this data analysis project is to process and present the reading and math scores of participants in a structured manner that respects their privacy while providing insightful analysis. This project entails the utilization of Microsoft Excel as a data management tool, where the raw data in the original spreadsheets will be transformed into a more manageable format. By reducing the amount of data shown, it will enhance the interpretability of charts and graphs for readers.

Initially, we need to organize the data based on participant performance in reading and math, both pre and post program participation. The aim is to reevaluate each participant’s change in skill level with the program's intervention. The major focal points of this analysis will be the 'Math Level (PRE)', 'Math Level (POST)', 'Reading Level (PRE)', and 'Reading Level (POST)'.

To begin, I will create a new Excel worksheet. This will serve as the simplified table for our participant data. The first step involves listing down participant information such as First Name, Age at Enrollment, Grade Level at Enrollment, and their respective test scores both before and after program completion.

After organizing the data into a simple table format, I will proceed to analyze the changes in reading and math levels pre and post program participation. To do this, I will calculate the averages of reading and math scores for participants before and after the program.

Upon calculating these averages, I will create visual representations to enhance understanding. Specifically, I will create bar charts that illustrate the average reading scores before and after the program and similar charts for math scores. Excel allows me to select the appropriate type of chart that best represents the data, and once I create these charts, I will ensure that they include proper labels for clarity.

For example, let’s assume the average math level for participants before the program is calculated at an average of 1.5 and after the program at 2.5. This notable increase can be illustrated using a bar chart where the x-axis represents the program participation and the y-axis represents the average scores. Each bar would represent the average scores for 'Math Level (PRE)' versus 'Math Level (POST)', conveying significant changes attributable to the program.

The same procedure will be followed for the reading scores. After creating these charts, they will be imported into a Word document where they can accompany a narrative that will explain the findings in detail.

Finally, I will include a discussion section where I interpret the implications of the findings. This includes reflecting on what the results mean for future programming, particularly the significance of improving average scores in both reading and math as indicative of student success. By analyzing pre- and post-participation data, the project will highlight the overall effectiveness of the program in fostering educational development among participants.

References

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• Miller, J. (1976). "Leadership Life Skills Development Scale: Applying the concept".
• Report of the National Reading Panel (2000). "Teaching Children to Read".
• National Center for Education Statistics. (2021). "The Condition of Education".
• Harvard Family Research Project. (2011). "Evaluating Family Engagement in Schools".
• American Institutes for Research. (2020). "Assessing the Impact of Programs".
• Johnson, R. B., & Onwuegbuzie, A. J. (2004). "Mixed methods research: A research paradigm whose time has come".
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