MSBTE 313307 Statistical Modelling for Machine Learning is one of the most important courses in the 3rd Semester of the MSBTE K Scheme Diploma curriculum. This subject is designed to give students an in-depth understanding of statistical concepts and their application in machine learning models. It helps students to learn how mathematical and statistical techniques are used for data analysis, prediction, and decision making.

Importance of Statistical Modelling For Machine Learning

• Builds a strong foundation in statistics, probability, and data analysis.
• Provides skills to apply statistical distributions and hypothesis testing in real datasets.
• Enables students to train, test, and validate machine learning models.
• Helps in developing predictive and analytical thinking required in data science.
• Enhances practical knowledge of tools like Python and R for statistical analysis.

Key Features of Lab Manual Answers

1. Step-by-step explanation of each experiment.
2. Well-structured programs in Python/R with clear outputs.
3. Easy-to-understand explanations of statistical distributions, tests, and models.
4. Practical viva questions and answers for exam preparation.
5. Written in student-friendly, exam-oriented format.

Topics Covered in MSBTE 313307 Lab Manual

• Basics of Descriptive and Inferential Statistics
• Probability distributions (Normal, Binomial, Poisson, Chi-Square, etc.)
• Hypothesis testing and confidence intervals
• Correlation and Regression analysis
• ANOVA (Analysis of Variance)
• Chi-Square Test and Goodness of Fit
• Implementation of statistical models in Python/R
• Applications of statistical modelling in machine learning

MSBTE External Basic Practical Viva/Oral Questions with Answers

Here are Some Basic Practical Viva/Oral Questions with Simple Answers for MSBTE External VIVA/Oral Question and Answers K Scheme Computer/AI/ML/IT Engineering 3rd Semester from MSBTE 313307 Statistical Modelling for Machine Learning Manual Answers or MSBTE 313307 SMML Lab Manual Answers:

Basic Questions

1. Q: What is statistical modelling?
   A: It is the process of applying statistical methods to represent real-world data and make predictions.
2. Q: Why is statistics important in machine learning?
   A: Statistics helps in analyzing data, understanding patterns, and validating models.
3. Q: Difference between descriptive and inferential statistics?
   A: Descriptive statistics summarize data, while inferential statistics make predictions or conclusions from data.
4. Q: What is a probability distribution?
   A: It shows how probabilities are distributed over different possible values of a random variable.
5. Q: Name some common distributions used in machine learning.
   A: Normal, Binomial, Poisson, Exponential, Chi-Square.

Probability and Distributions

6. Q: What is the Normal distribution?
   A: It is a bell-shaped curve where most data points lie around the mean.
7. Q: What is the Binomial distribution?
   A: A distribution showing the probability of success in a fixed number of trials.
8. Q: What is the Poisson distribution?
   A: It models the number of events occurring in a fixed interval of time or space.
9. Q: What is standard deviation?
   A: It measures how much data values deviate from the mean.
10. Q: What is variance?
    A: It is the square of standard deviation, representing data spread.

Hypothesis Testing

11. Q: What is hypothesis testing?
    A: It is a method of making decisions about population parameters based on sample data.
12. Q: What is null hypothesis?
    A: A statement that there is no significant difference or effect.
13. Q: What is alternative hypothesis?
    A: A statement that there is a significant effect or difference.
14. Q: What is p-value?
    A: The probability of obtaining results as extreme as the observed ones, under the null hypothesis.
15. Q: When do we reject the null hypothesis?
    A: If the p-value is less than the significance level (α).

Correlation and Regression

16. Q: What is correlation?
    A: It measures the strength and direction of relationship between two variables.
17. Q: What is regression analysis?
    A: It predicts the value of a dependent variable based on independent variables.
18. Q: Difference between correlation and regression?
    A: Correlation measures relationship, regression predicts values.
19. Q: What is simple linear regression?
    A: It predicts outcomes using one independent variable.
20. Q: What is multiple regression?
    A: It predicts outcomes using two or more independent variables.

ANOVA and Chi-Square

21. Q: What is ANOVA?
    A: Analysis of Variance, used to compare means of multiple groups.
22. Q: What is Chi-Square test?
    A: A statistical test used to check independence or goodness of fit.
23. Q: Where is Chi-Square test applied?
    A: In categorical data analysis, independence testing, and model fitting.
24. Q: What is F-test?
    A: A test used to compare variances between groups.
25. Q: Why is ANOVA important in machine learning?
    A: It helps identify which factors significantly affect the outcome.

Machine Learning Applications

26. Q: How is probability used in machine learning?
    A: It helps in building models like Naive Bayes classifier.
27. Q: What is overfitting in statistical modelling?
    A: When a model fits training data too closely and fails on new data.
28. Q: What is underfitting?
    A: When a model is too simple and fails to capture data patterns.
29. Q: What is the role of statistical modelling in ML?
    A: It ensures accuracy, generalization, and interpretability of models.
30. Q: Name some machine learning models using statistics.
    A: Linear regression, Logistic regression, Naive Bayes, Decision Trees.

FAQs on MSBTE 313307 Statistical Modelling For Machine Learning Lab Manual

Q1. Where can I find MSBTE 313307 Statistical Modelling For Machine Learning Lab Manual Answers K Scheme 3rd Semester?
A1. You can get all lab manual answers in handwritten style at www.diplomasolution.com.

Q2. Are the lab manual answers helpful for exam preparation?
A2. Yes, they cover programs, explanations, and viva questions useful for practical and theory exams.

Q3. Does the manual include statistical programs in Python/R?
A3. Yes, it includes Python/R programs with detailed explanations.

Q4. How to Download this Lab Manual Answers PDF?
A4. You can download it directly from www.diplomasolution.com.

Q5. How to download all IMP exam questions?
A5. All important exam questions are available at www.diplomasolution.com.