Regression Analysis | Fresco Play

Question 1: Based on the hands on card “ OLS in Python Statsmodels” What is the value of the estimated coef for variable RM ?

Answer: 9.1021

Question 2: Based on the hands on card “ OLS in Python Statsmodels”What is the value of the constant term ?

Answer: -34.6706

Question 3: Based on the hands on card “ OLS in Python Statsmodels” What is the adjusted R sq value ?

Answer: 0.483

Question 4: Based on the hands on card “ OLS in Python Statsmodels” What is the value of R sq ?

Answer: 0.484

Question 5: Based on the hands on card “ OLS in Python Statsmodels” How many observations are there in the dataset ?

Answer: 506

Question 6: Based on the hands on card “MLR Hands On” Perform a correlation among all the independent variables . What is the correlation between variables NOX and DIS ?

Answer: -0.76923

Question 7: Based on the hands on card “MLR Hands On” What is the P>|t| value for the 'INDUS' variable ?

Answer: 0.731

Question 8: Based on the hands on card “MLR Hands On” What is the standard error for the constant term ?

Answer: 5.104

Question 9: Based on the hands on card “MLR Hands On” What is the value of the estimated coef for the constant term ?

Answer: 36.4911

Question 10: Based on the hands on card “MLR Hands On” what is the value of R sq ?

Answer: 0.741

Question 11: Regression can show causal relationship between two variables.

Answer: False

Question 12: In Multi Variable regression you predict one variable using more than one variable

Answer: True

Question 13: The SSE depends on the number of observations in the data set

Answer: True

Question 14: __________ means predicting one variable from another.

Answer: Regress

Question 15: What is the process of removing the mean and dividing the value by the standard deviation

Answer: Standatdization

Question 16: __________ is a unit less quantity

Answer: R Square

Question 17: When two or more variables are correlated in a Multiple Regression Model , it is called as ____________

Answer: Multi Collinearity

Question 18: What is the process of rescaling the values in the range [0,1]

Answer: Normalization

Question 19: What is the formula for root means square error ?

Answer: sqrt(SSE/n)

Question 20: It is advised to omit a term that is highly correlated with another while fitting a Multiple Regression Model

Answer: True

Question 21: When more variables are added in Multi Variable Regression the marginal improvement decreases as each variable is added. This term is called ?

Answer: Law of Diminishing Returns

Question 22: R Square Value can be greater than zero

Answer: False

Question 23: Arithmetic Mean can be used as a prediction measure.

Answer: True

Question 24: What is the sum of standard error for the baseline model ?

Answer: SST

Question 25: SSE is _________ for the Line of Best Fit and _______ for the baseline model

Answer: Small , Big

Question 26: It is advised to go for a simpler model while fitting multiple regression for a dataset

Answer: True

Question 27: What is the term that represents the difference between actual and predicted value called ?

Answer: Residual

Question 28: What is the basic property of the model of best fit ?

Answer: Minimize Error

Question 29: By adding multiple variables in Multi Variable Regression , the model accuracy _____________

Answer: Increases

Question 30: Sum of Squared error is a measure of standard for a Regression Line

Answer: True

Question 31: What is the good range of correlation values to include in the regression model

Answer: -0.7 to + 0.7

Question 32: What is the quantity that measures the strength of relationship between two variables ?

Answer: Correlation

Question 33: pr(>|t|) term signifies how likely the estimated value is zero

Answer: True

Question 34: It is OK to discard theoretical considerations for Statistical Measures

Answer: False