Your roadmap · आपका रोडमैप
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Admission & first meetingप्रवेश और पहली मुलाकातEnquire at your nearest NDSS centre, meet the teacher, fix the batch time and get your study material.
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Part 1 of the syllabusपाठ्यक्रम भाग 1Unit-wise coaching with notes and doubt classes.
Unit 1: Descriptive StatisticsUnit 2: Probability and DistributionsUnit 3: Statistical Inference
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Part 2 of the syllabusपाठ्यक्रम भाग 2Unit-wise coaching with notes and doubt classes.
Unit 4: Correlation and RegressionUnit 5: Statistical Computing with R and Python
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Unit tests & assignmentsयूनिट टेस्टRegular tests in the university / board pattern.
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Semester 5 exam (university / board)विश्वविद्यालय / बोर्ड परीक्षाPrevious papers and full revision before the exam.
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Online tests & resultऑनलाइन टेस्ट और रिज़ल्टTake the tests online; your marks and result show in your student login and at the centre.
सिलेबस · पाठ्यक्रम
1 subject · 5 chapters · 26 topics
01Unit 1: Descriptive Statistics
5 टॉपिक+
- Types of data and scales of measurement
- Frequency distributions and graphs
- Mean, median and mode
- Range, variance and standard deviation
- Skewness and kurtosis
02Unit 2: Probability and Distributions
5 टॉपिक+
- Probability, conditional probability and Bayes' theorem
- Random variables, expectation and variance
- Binomial and Poisson distributions
- Normal distribution
- Sampling distributions and central limit theorem
03Unit 3: Statistical Inference
5 टॉपिक+
- Point and interval estimation
- Hypothesis testing, type I and type II errors
- z-test and t-test
- Chi-square test
- F-test and one-way ANOVA
04Unit 4: Correlation and Regression
6 टॉपिक+
- Scatter diagram and Karl Pearson's correlation
- Spearman's rank correlation
- Simple linear regression by least squares
- Multiple linear regression
- Coefficient of determination and residual analysis
- Introduction to logistic regression
05Unit 5: Statistical Computing with R and Python
5 टॉपिक+
- R basics: vectors, data frames, functions
- Python: NumPy, pandas, SciPy and statsmodels
- Data import, cleaning and visualisation (ggplot2, matplotlib)
- Random number generation and simulation
- Monte Carlo methods and bootstrap
About this course
आप यह कर पाएँगे
- Summarise data with measures of central tendency, dispersion, skewness and kurtosis
- Apply probability rules and binomial, Poisson and normal distributions
- Construct confidence intervals and perform z, t, chi-square, F tests and ANOVA
- Compute correlation and fit simple and multiple linear regression models
- Use R and Python (pandas, NumPy, SciPy, statsmodels) for data analysis and visualisation
- Use simulation, Monte Carlo and bootstrap methods
यह किसके लिए है
- B.Tech Computer Science & Engineering students of Semester 5 (AKTU)
- Students of other universities studying the same subject who want unit-wise coaching
आपको क्या चाहिए
- Engineering mathematics (probability basics)
- Basic programming in Python or R
Online tests & result
Practice and unit tests online; marks and result show in your student login and at the centre.
Student login →
सवाल
Which syllabus does the Statistical Computing course follow?
It follows the AKTU (Dr. A.P.J. Abdul Kalam Technical University, Lucknow) B.Tech syllabus for Statistical Computing. If your own university's syllabus differs, the centre follows your university syllabus.
Will this help in the university examination?
Yes. Teaching is unit-wise as per the AKTU scheme, with previous-year question practice, MCQ tests and doubt sessions before the semester exam.
Will I learn R or Python?
Both are introduced; every statistical method is first solved by hand and then computed in R and Python.
