MATLAB: An Introduction with Applications
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ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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We recorded the pre-statistics course grade (in percent) and introductory statistics course grade (in percent) for 60 community college students.
In this data set, no one earned a 90% for the pre-statistics course grade. How could you estimate a student’s introductory statistics course grade if she earned 90% for the pre-statistics course grade?
A. Substitute 90 into the regression equation: Predicted introductory statistics course grade = -0.147 + 0.981(90) .
B. Substitute the decimal 0.90 into the regression equation: Predicted introductory statistics course grade = -0.147 + 0.981(0.90).
Transcribed Image Text:The image presents a scatter plot depicting the relationship between grades in a Pre-statistics course and an Introductory Statistics course.
### Description:
- **X-axis (Horizontal):** Represents the Pre-statistics Course Grade, measured in percent, ranging from 70 to 95.
- **Y-axis (Vertical):** Represents the Introductory Statistics Course Grade, also measured in percent, ranging from 55 to 95.
- **Data Points:** Each blue dot corresponds to a student's performance, showing the link between their Pre-statistics and Introductory Statistics grades.
- **Trend Line:** A red line of best fit is drawn through the data points, indicating a positive correlation. This suggests that higher grades in the Pre-statistics course are generally associated with higher grades in the Introductory Statistics course.
### Analysis:
The scatter plot highlights a positive linear relationship between the grades in the two courses, implying that students who perform well in the Pre-statistics course also tend to achieve higher grades in the subsequent Introductory Statistics course. This pattern suggests the potential importance of foundational knowledge for success in more advanced statistical coursework.
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