Information Technology Engineering Sem 6 Stat Learning For Data Science Honours Question Paper PDF 2026 - Mumbai University | munotes
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Paper Subject Code: 48847 Honours/Minor degree programs Statistical Learning for Data Science
N.B.: (1) Question No 1 is Compulsory
(2) Attempt any three questions out of the remaining five
(3) All questions carry equal marks
(4) Assume suitable data, if required and state it clearly
1 Attempt any FOUR [20]
a Explain Categorical data and quantitative data
S.D of the average temperature recorded over a five-day period last winter
c Define Binomial distribution and Poisson distribution
d Explain Typel and Type 2 error in detail
e Define the following key terms for simple linear regression
2 scored in a cricket match by 11 players are as [10]
Find mean, mode, median for the given data
An agent sells life insurance policies to five equally aged healthy people. [10]
According to recent data, the probability of a person living in these conditions
for 30 years or more is the probability that after 30 years if
1) All five people are still living
li) At least three people are still living
ili) Exactly two people are still living (Hint: Binomial Distribution)
a Xisanormally distributed variable with mean S. D o=4.Find 1) P(X<40) [10]
the steps in multinomial distribution goodness of fit. Elaborate the steps [10]
with an example
4 Brief the steps in test of independence. Elaborate the steps with an example [10]
Find the simple linear regression that fits the given data and co efficient of [10]
Paper Subject Code: 48847 Honours/Minor degree programs Statistical Learning for Data Science
5 Inthe context of multiple linear regression. Explain what is over fitting and multi [10]
Predict equation for y. [10]
6 Explain TIME SERIES PATTERNS [10]
iv)Trend and Seasonal Pattern v)Cyclical Pattern
Consider the following time series data. [10]
Using the naive method (most recent value) as the forecast for the next week,
compute the following measures of forecast accuracy
iii) Mean absolute percentage error. iv) Determine the forecast for week 7?
N.B.: (1) Question No 1 is Compulsory
(2) Attempt any three questions out of the remaining five
(3) All questions carry equal marks
(4) Assume suitable data, if required and state it clearly
1 Attempt any FOUR [20]
a Explain Categorical data and quantitative data
S.D of the average temperature recorded over a five-day period last winter
c Define Binomial distribution and Poisson distribution
d Explain Typel and Type 2 error in detail
e Define the following key terms for simple linear regression
2 scored in a cricket match by 11 players are as [10]
Find mean, mode, median for the given data
An agent sells life insurance policies to five equally aged healthy people. [10]
According to recent data, the probability of a person living in these conditions
for 30 years or more is the probability that after 30 years if
1) All five people are still living
li) At least three people are still living
ili) Exactly two people are still living (Hint: Binomial Distribution)
a Xisanormally distributed variable with mean S. D o=4.Find 1) P(X<40) [10]
the steps in multinomial distribution goodness of fit. Elaborate the steps [10]
with an example
4 Brief the steps in test of independence. Elaborate the steps with an example [10]
Find the simple linear regression that fits the given data and co efficient of [10]
Paper Subject Code: 48847 Honours/Minor degree programs Statistical Learning for Data Science
5 Inthe context of multiple linear regression. Explain what is over fitting and multi [10]
Predict equation for y. [10]
6 Explain TIME SERIES PATTERNS [10]
iv)Trend and Seasonal Pattern v)Cyclical Pattern
Consider the following time series data. [10]
Using the naive method (most recent value) as the forecast for the next week,
compute the following measures of forecast accuracy
iii) Mean absolute percentage error. iv) Determine the forecast for week 7?
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Information Technology Engineering Sem 6 Paper Path
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