STA301: Statistics and Probability
STA301 Statistics and Probability teaches you to collect, describe and draw conclusions from data. It covers frequency tables and graphs, averages and spread, probability, random variables, binomial and normal distributions, sampling and hypothesis testing.
- 45 lectures
- Past papers style solved MCQs
- Answers in English and Roman Urdu
How to prepare for STA301
STA301 Lecture Quizzes
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STA301 Exam Mocks
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STA301 Statistics and Probability
Gradup covers all 45 lectures of STA301 Statistics and Probability with Past Papers Style Solved MCQs. Use the lecture quizzes while you study the STA301 handouts, then switch to the STA301 midterm and final term mocks. Every answer comes with an explanation and the handout reference, so you know exactly where to revise.
- 01Data and frequency distributions
- 02Mean, median and mode
- 03Measures of dispersion
- 04Probability
- 05Binomial and normal distributions
- 06Sampling and hypothesis testing
See all 45 STA301 lectures
- 1 STA301 Lecture 1Introduction
- 2 STA301 Lecture 2Types of Data and Sampling
- 3 STA301 Lecture 3Graphical Representation of Data
- 4 STA301 Lecture 4Construction of Frequency Distribution
- 5 STA301 Lecture 5Types of Frequency Curves
- 6 STA301 Lecture 6Stem and Leaf Plot and Introduction to Measures of Central Tendency
- 7 STA301 Lecture 7Arithmetic Mean, Weighted Mean and Median
- 8 STA301 Lecture 8Empirical Relation between Mean, Median and Mode, and Quantiles
- 9 STA301 Lecture 9Geometric Mean, Harmonic Mean and the Relationship between Them
- 10 STA301 Lecture 10Measures of Dispersion
- 11 STA301 Lecture 11Mean Deviation, Standard Deviation, Variance and Coefficient of Variation
- 12 STA301 Lecture 12Chebychev’s Inequality, the Empirical Rule and the Five-Number Summary
- 13 STA301 Lecture 13Box and Whisker Plot, Pearson’s Coefficient of Skewness
- 14 STA301 Lecture 14Moments, Skewness and Kurtosis
- 15 STA301 Lecture 15Correlation and Regression
- 16 STA301 Lecture 16Set Theory and Counting Rules
- 17 STA301 Lecture 17Permutations and Combinations
- 18 STA301 Lecture 18Definitions of Probability
- 19 STA301 Lecture 19Relative Frequency, Axiomatic Definition and Laws of Probability
- 20 STA301 Lecture 20Application of Addition Theorem, Conditional Probability and Multiplication Theorem
- 21 STA301 Lecture 21Independent and Dependent Events, Multiplication Theorem and Marginal Probability
- 22 STA301 Lecture 22Bayes’ Theorem, Discrete Random Variable
- 23 STA301 Lecture 23Graphical Representation of the Distribution Function of a Discrete Random Variable
- 24 STA301 Lecture 24Chebychev’s Inequality and Concept of Continuous Probability Distribution
- 25 STA301 Lecture 25Continuous Probability Distribution, Bivariate Probability Distribution
- 26 STA301 Lecture 26Bivariate Probability Distributions and Properties of Expected Values
- 27 STA301 Lecture 27Properties of Expected Values, Covariance, Correlation and Discrete Probability Distributions
- 28 STA301 Lecture 28Binomial Distribution, Introduction to the Hypergeometric Distribution
- 29 STA301 Lecture 29Hypergeometric Distribution, Poisson Distribution and Continuous Uniform Distribution
- 30 STA301 Lecture 30Normal Distribution
- 31 STA301 Lecture 31Sampling Distribution, Central Limit Theorem
- 32 STA301 Lecture 32Sampling Distributions
- 33 STA301 Lecture 33Sampling Distribution, Point Estimation and Desirable Qualities of a Good Point Estimator
- 34 STA301 Lecture 34Qualities of a Good Point Estimator, Methods of Point Estimation and Interval Estimation
- 35 STA301 Lecture 35Confidence Interval
- 36 STA301 Lecture 36Large Sample Confidence Intervals, Determination of Sample Size and Hypothesis Testing
- 37 STA301 Lecture 37Hypothesis Testing (Part 2)
- 38 STA301 Lecture 38Hypothesis Testing regarding μ1-μ2 and p (Z-statistic)
- 39 STA301 Lecture 39Hypothesis Testing regarding p1-p2 and the Student’s t-distribution
- 40 STA301 Lecture 40Tests and Confidence Intervals based on the t-distribution
- 41 STA301 Lecture 41Hypothesis Testing regarding Two Population Means and the Chi-square Distribution
- 42 STA301 Lecture 42The F-Distribution, Hypothesis Testing and Interval Estimation
- 43 STA301 Lecture 43Analysis of Variance and Experimental Design
- 44 STA301 Lecture 44Randomized Complete Block Design, (LSD) Test and Chi-Square Test of Goodness of Fit
- 45 STA301 Lecture 45Chi-Square Test, p-value and the Latest Definition of Statistics
Frequently asked questions
Quick answers about practising STA301 on Gradup.
Gradup has lecture-wise STA301 quizzes with Past Papers Style Solved MCQs covering all 45 lectures, with explanations in English and Roman Urdu.
Yes. Choose the lectures that are in your midterm and Gradup builds a STA301 midterm mock from Past Papers Style Solved MCQs of only those lectures. Try again for other questions from the same lectures.
Yes. The STA301 final term mock mixes easy, medium and hard MCQs from the lectures you select, just like the real paper.
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