BIT · Semester II
Basic Statistics syllabus
Official TU syllabus for Basic Statistics (STA154): 9 units, 63 topics. Every unit links to its notes and solved questions.
1
Introduction to Statistics and Data
10 Q- Definition and role of statistics in IT
- Descriptive versus inferential statistics
- Primary and secondary data sources
- Measurement scales and types
- Population and sample concepts
- Parameter and statistic distinction
2
Data Collection and Sampling Methods
3 Q- Census and sample surveys
- Sampling techniques and methods
- Stratified sampling
- Cluster sampling
- Sampling error and non-sampling error
- Sample size determination
3
Data Presentation and Visualization
11 Q- Frequency distributions and tables
- Histogram construction
- Frequency polygon and frequency curve
- Bar diagrams and Pareto diagrams
- Pie charts
- Box and whisker plots
- Five number summary
4
Measures of Central Tendency and Dispersion
6 Q- Mean, median, and mode
- Choice of appropriate central tendency measure
- Range and interquartile range
- Variance and standard deviation
- Coefficient of variation
- Methods of measuring dispersion
- Comparison of consistency between datasets
5
Moments, Skewness, and Kurtosis
6 Q- Central moments and raw moments
- Computation of moments from data
- Coefficient of skewness
- Mesokurtic, platykurtic, and leptokurtic distributions
- Coefficient of kurtosis
- Interpretation of skewness and kurtosis
6
Probability and Probability Distributions
27 Q- Basic probability concepts and rules
- Conditional probability and Bayes theorem
- Random variables and probability functions
- Discrete probability distributions
- Binomial distribution
- Poisson distribution
- Continuous probability distributions
- Normal distribution properties and applications
- Standard normal distribution and Z-scores
7
Sampling Distributions and Estimation
7 Q- Sampling distribution of mean
- Central limit theorem
- Point estimation
- Interval estimation and confidence intervals
- Confidence interval for population mean
- Confidence interval for population proportion
- Interpretation of confidence intervals
8
Correlation and Regression Analysis
12 Q- Correlation coefficient definition and properties
- Karl Pearson correlation coefficient
- Spearman rank correlation coefficient
- Interpretation of correlation results
- Simple linear regression model
- Regression equation fitting
- Regression coefficient interpretation
- Estimation using regression equations
- Assumptions of linear regression
9
Statistical Hypothesis Testing and Applications
2 Q- Hypothesis testing concepts
- Type I and Type II errors
- Test selection based on measurement scale
- Application of statistics in IT systems
- Quality control and reliability analysis
- Expected value and decision making
Study STA154 the smart way
Solved questions, flashcards & practice