NPTEL Learning Analytics Tools Week 8 Assignment Answers 2024

1. In the context of educational data which of the following need not to be similar to perform predictive analytics. Choose the most appropriate answer. (You can refer Lecture 44 Week 8).

Domain
Interaction behavior
Interaction time
Number of Students

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2. How predictive analytics is different from Descriptive and Diagnostic Analytics? (Choose the most appropriate answer).

Predictive Analytics focuses on summarizing past data, while Descriptive Analytics focuses on predicting future trends
Predictive Analytics identifies the root causes of past events, whereas Diagnostic Analytics forecasts potential outcomes
Predictive Analytics focuses on using past data to forecast future outcomes, while Descriptive and Diagnostic Analytics focus on understanding and explaining past events
Predictive Analytics is concerned with real-time data analysis, while Descriptive and Diagnostic Analytics are only concerned with historical data

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3. What is the primary difference between Simple Linear Regression and Multiple Linear Regression?

Simple Linear Regression can only model non-linear relationships, while Multiple Linear Regression can model linear relationships
Simple Linear Regression uses one dependent variable, while Multiple Linear Regression uses multiple dependent variables
Simple Linear Regression uses one independent variable, while Multiple Linear Regression uses two or more independent variables
Simple Linear Regression and Multiple Linear Regression are identical techniques with different names

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4. In which scenario is Multivariate Regression preferred over Multiple Linear Regression?

When there are multiple independent variables and only one dependent variable
When the relationship between the variables is non-linear
When there are multiple dependent variables being predicted simultaneously
When the dataset is very large and needs to be reduced

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5. How does Logistic Regression differ from Linear Regression?

Logistic Regression is used for predicting continuous outcomes, while Linear Regression is used for categorical outcomes
Logistic Regression uses a logistic function to model binary outcomes, while Linear Regression models continuous outcomes
Logistic Regression requires multiple independent variables, while Linear Regression only requires one
Logistic Regression is more accurate than Linear Regression for all types of data.

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6. If you have multiple linear regression models for the given data how can you find out which model is best out of given models? (Choose the most appropriate answer).

By manually looking at points and find out which line is closest to maximum number of points
By comparing mean square value for each model and selecting whose mean square value is minimum
By comparing mean square value for each model and selecting whose least mean square value is maximum
By calculating the slope of all lines and comparing them

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7. In educational settings what is the meaning of intercept in linear regression? (Choose the most appropriate answer).

It specifies the minimum value of the dependent variable
It specifies the minimum value of the independent variable
It is not recommended to find out the exact meaning of intercept in educational settings
It specifies exactly at what is the scale of the relationship between independent and dependent variable

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8. Which of the following is a correct use case for Logistic Regression in an educational setting?

Predicting a student’s exact score on a final exam based on study hours
Classifying whether a student will pass or fail a course based on their attendance and assignment scores
Estimating the number of students who will attend a workshop based on previous attendance rates
Modeling the relationship between study hours and final exam scores in a continuous scale

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9. Consider the equation: Y=c+X1W1+X2W2. Here what is the significance of W1 and W2? (Choose the most appropriate answer).

W1 specifies the relation between X1 and Y keeping all other values constant
W2 specifies the relation between X1 and Y keeping all other values constant
W2 specifies the relation between X2 and Y keeping all other values constant
W1 specifies the relation between X2 and Y keeping all other values constant

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10. A Linear Regression model is used to predict a student’s final exam score based on the number of hours they study. The model is given by the equation: Final Exam Score=40+5×(Study Hours). If a student studies for 8 hours, what is their predicted final exam score?