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19a. For number of interrruptions (x) ____________ MX= (2 decimal places)  19b. For number of interruptions (x) ____________ SSx = (use 4 dec. places during calculation; report 1 dec. place) 19c. For time spent on task ____________ My  = (1 dec. place)

19a. For number of interrruptions (x) ____________ MX= (2 decimal places)  19b. For number of interruptions (x) ____________ SSx = (use 4 dec. places during calculation; report 1 dec. place) 19c. For time spent on task ____________ My  = (1 dec. place)

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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19a. For number of interrruptions (x) ____________

MX= (2 decimal places) 

19b. For number of interruptions (x) ____________

SSx = (use 4 dec. places during calculation; report 1 dec. place)

19c. For time spent on task ____________

My  = (1 dec. place)

The table below displays data on the correlation between the number of interruptions and the time spent on a task. The data is organized into two columns: "Number of Interruptions" and "Time Spent on Task." | Number of Interruptions | Time Spent on Task | |-------------------------|--------------------| | 8 | 18 | | 3 | 40 | | 6 | 20 | | 2 | 32 | This table suggests a potential relationship between how frequently tasks are interrupted and the duration required to complete them. For instance, with 8 interruptions, the task took 18 units of time, while with only 2 interruptions, it took 32 units of time. This data could be used to analyze the effects of interruptions on productivity.
Transcribed Image Text:The table below displays data on the correlation between the number of interruptions and the time spent on a task. The data is organized into two columns: "Number of Interruptions" and "Time Spent on Task." | Number of Interruptions | Time Spent on Task | |-------------------------|--------------------| | 8 | 18 | | 3 | 40 | | 6 | 20 | | 2 | 32 | This table suggests a potential relationship between how frequently tasks are interrupted and the duration required to complete them. For instance, with 8 interruptions, the task took 18 units of time, while with only 2 interruptions, it took 32 units of time. This data could be used to analyze the effects of interruptions on productivity.
## Educational Exercise: Calculating Pearson Correlation Coefficient ### Overview A researcher investigates the relationship between the number of interruptions in a class and the time spent on a task (measured in minutes). The task is to compute the Pearson correlation coefficient using the provided data. ### Instructions 1. **Calculation Setup**: - Use your own paper to calculate the correlation coefficient. - Retain your calculations for reference. - Note: The provided e-text table may contain formatting errors. Use the r distribution available in Blackboard for accurate calculations. 2. **Data Entry**: Below are the values you will need to compute: - **2.1** Mean for number of interruptions (\(x\)) - **2.2** \(SS_x\) for number of interruptions - **2.3** Mean for time spent on task (\(y\)) - **2.4** \(SS_y\) for time spent on task - **2.5** Sum of Products (SP, \(SS_{xy}\)) - **2.6** Correlation coefficient (\(r\)) ### Explanation of Terms - **Mean**: The average value of a set of numbers. - **SS (Sum of Squares)**: A measure that captures how much individual values in a data set deviate from the mean. - **Sum of Products (SP)**: Calculated by multiplying corresponding deviations of two variables and summing the results. - **Correlation Coefficient (\(r\))**: A statistical measure of the strength and direction of a linear relationship between two variables. This exercise is designed to help you understand the practical application of statistical concepts such as means, variance, and correlation in real-world data analysis.
Transcribed Image Text:## Educational Exercise: Calculating Pearson Correlation Coefficient ### Overview A researcher investigates the relationship between the number of interruptions in a class and the time spent on a task (measured in minutes). The task is to compute the Pearson correlation coefficient using the provided data. ### Instructions 1. **Calculation Setup**: - Use your own paper to calculate the correlation coefficient. - Retain your calculations for reference. - Note: The provided e-text table may contain formatting errors. Use the r distribution available in Blackboard for accurate calculations. 2. **Data Entry**: Below are the values you will need to compute: - **2.1** Mean for number of interruptions (\(x\)) - **2.2** \(SS_x\) for number of interruptions - **2.3** Mean for time spent on task (\(y\)) - **2.4** \(SS_y\) for time spent on task - **2.5** Sum of Products (SP, \(SS_{xy}\)) - **2.6** Correlation coefficient (\(r\)) ### Explanation of Terms - **Mean**: The average value of a set of numbers. - **SS (Sum of Squares)**: A measure that captures how much individual values in a data set deviate from the mean. - **Sum of Products (SP)**: Calculated by multiplying corresponding deviations of two variables and summing the results. - **Correlation Coefficient (\(r\))**: A statistical measure of the strength and direction of a linear relationship between two variables. This exercise is designed to help you understand the practical application of statistical concepts such as means, variance, and correlation in real-world data analysis.
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