Statistical Modelling for Machine Learning (313307) MSBTE QuAn Question Answer Book

Description

QuAn Book – Statistical Modelling for Machine Learning (313307)

The QuAn Book for Statistical Modelling for Machine Learning (Subject Code: 313307) is a premium study material designed for MSBTE K-Scheme Diploma Engineering students. It provides a complete, topicwise question bank with model answers to help you score maximum marks.

Syllabus Coverage (MSBTE K-Scheme)

• Unit I – Statistical Techniques: Frequency Distribution: Definition, Basic terms; Classification of Data: Raw, Ungroup and Group data; Measures of Central Tendency: Mean, Median and Mode for all types of data; Concept of Quartiles, Deciles and Percentiles for all types of data; Geometric mean and Harmonic mean and Combined mean for given data; Graphical Representation to find Mode (Histogram) and Median (Ogive curve); Measures of Dispersion: Range, Mean Deviation, Standard Deviation, Variance; Skewness: Types of skewness, Test of skewness, Co-efficient of skewness-Karl Pearson’s and Bowley’s coefficient; Types of skewness in terms of Mean and Mode; Measures of Kurtosis using central moment
• Unit II – Statistical Methods: Fitting of Straight Line y = a+bx using method of least square; Fitting of second degree polynomial y=a+bx+cx^2 using method of least square; Covariance of the data; Correlations, Types of Correlations; Scatter Or Dot-Diagram; Karl-Pearson’s and Spearman’s Rank Coefficient of Correlation; Regression Equation of line in two variables
• Unit III – Probability of Random Variable: Probability: Definition, Terminologies; Theorem of Probability: Addition, Multiplication; Conditional probability; Bayes’ theorem
• Unit IV – Interpolation: Introduction; Lagrange’s Interpolation formula; Finite Differences: Forward difference, Backward difference, Shift operator, Inverse shift operator; Relation between forward, backward, shift and inverse shift operator; Newton’s Gregory forward and backward difference Interpolation Formula; Concept of Extrapolation
• Unit V – Sampling Methods: Population, Sampling, Aim of Sampling, Parameters and Statistic, Types of Sampling, Standard Error; Hypothesis: Null Hypothesis and Alternating Hypothesis; Level of Significance, Test of Significance and Confidence Limits; Test of Significance of Large Samples (N>30); Sample Distribution of the proportion; Comparison of Large Samples; The t-Distribution (For Small Samples); Chi-Square Distribution, Condition for Chi Square test; Degree of freedom; Chi-Square Test of Goodness of fit and Chi-Square test as a test of Independence

What’s Inside the QuAn Book?

• Topicwise Question Bank – All important 2, 4 and 6 marks questions by unit
• Model Answers – Step-by-step solutions with diagrams and marking scheme
• Previous Exam Questions – Actual MSBTE Summer and Winter exam questions
• Frequency Analysis – Most repeated questions highlighted for focused study
• Marking Scheme – Know exactly what to write to score full marks
• Last Minute Ready – Ideal for quick and focused exam preparation

Subject Code: 313307 | Subject: Statistical Modelling for Machine Learning | Board: MSBTE | Scheme: K Scheme | Published by: ReemaS Edutech, Kolhapur