# Quantitative reasoning i project: creating visuals from data

Posted: October 14th, 2021

The purpose of this assignment is to have you practice creating visuals using the data from the topic you chose in Week 2. Creating charts and trendlines are important skills used in many careers.- I chose  health services and nursing scenario

Watch Week 4 Lynda.com® Video: Data-Analysis Fundamentals with Excel.

Create at least two visuals using your data from the data you chose in Week 2.

1. Create one scatter plot of the data, and apply a linear model (also known as a regression) in Excel®. Include the equation, R2 value, and prediction value on the visual.
2. Create one scatter plot of the data, and apply an exponential model in Excel®. Include the equation, R2 value,  and prediction value on the visual.
3. Determine whether the linear or the exponential model is a better representation of your data to base your prediction on. Explain why the model you chose is a better representation of your data.

Hints for Making an Effective Chart:

• Decide why you are making a chart from this data.
• Title each chart so that it aligns with the data and selected model.
• Create descriptive labels for both the x- and y axes.
• Resize the chart as needed so it can be viewed easily.

Select the Assignment Files tab to submit your visuals as either an Excel® file or a Word document.

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Week 4 Grading Guide: Creating Visuals from Data
Mathematical Computations (40%) Points Earned: x.x/4
There is a sound demonstration of ability to perform mathematical computations.
There is an accurate summarization of data.
There is clear reasoning as to why the regression was chosen.
Creating Visuals (60%) Points Earned: x.x/6
At least two visuals are included.
The visuals demonstrate sound skill in the creation of scatter plots to show their ability to use mathematical principles to interpret math forms.
The scatter plots have proper labeling on both the x- and y- axes.
The visuals have a proper heading (linear regression, exponential regression, polynomial regression).
The visuals have made use of either the linear model, exponential models, or polynomial models.
The R2 and Prediction values and model equations are present.