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MATH 2310

Elementary Probability and Statistics

0.5 credits · Undergraduate

Fall 2025

Topics

  • events, elementary probability, descriptive statistics using tables and charts, measures of central tendency
  • variability and association, basic discrete and continuous distributions, sampling distributions, hypothesis
  • Successful students of this course
  • Understand the basic concepts and terminologies used in probability and statistics
  • Able to identify the type of data
  • Summarize the data using charts and tables and interpret the findings
  • Calculate the measures of central tendency, variability, and association
  • Understand some basic concept in probability such as sample space and event, event operations
  • conditional probability
  • Understand the concept of independent events and to apply our understanding of independent
  • events to real-life scenarios
  • Calculate probabilities using (discrete) probability distribution tables and (continuous)
  • probabilities density functions
  • Become familiar with discrete distributions including Binomial, Hypergeometric, Poisson, etc
  • Become familiar with continuous distributions including normal, uniform, exponential, etc
  • Find probabilities by using normal distribution to approximate binomial distribution
  • Find sampling distributions of sample means and probabilities using the Central Limit Theorem
  • constructing confidence intervals
  • Find the correlation between two random variables and interpret the correlation

Readings

  • Statistics, 13th Edition by James T. McClave and Terry Sincich Paper copies of this
Fall 2025

Topics

  • ˆ Beginnings of Statistical Analysis
  • – Understand the difference between descriptive and inferential statistics
  • – Interpret frequency tables and graphs and use them to summarize various data sets
  • ˆ Elementary Probability
  • – Understand the notion of a sample space, event, and compound event
  • – Compute classical and empirical probabilities
  • – Identify mutually exclusive and independent events
  • – Apply the Addition and Multiplication Rules to compute probabilities
  • – Understand and be able to compute conditional probabilities
  • – Apply counting rules to compute probabilities of more complex events
  • ˆ Random Variables and Probability Distributions
  • – Understand the notion of a (discrete/continuous) random variable and probability distri
  • bution
  • variation (variance, standard deviation) for data sets
  • – Utilize basic discrete distributions (binomial, Poisson, hypergeometric) to compute corre
  • sponding probabilities
  • – Utilize basic continuous distributions (uniform, normal) to compute corresponding prob
  • abilities
  • – Use z-scores and percentiles to identify the position of a data value in relation to its data
  • – Be familiar with empirical rules for the normal distribution

Readings

Winter 2025

Topics

  • Statistical Terminology
  • Sampling Procedures
  • Organizing Data
  • Histograms, Frequency Polygons
  • Measures of Central Tendency
  • Measures of Location
  • Sample Spaces and Probability
  • Addition and Multipli
  • Probability Distributions
  • Mean, Variance, and Expec
  • Normal Distributions and Applications
  • Central Limit
  • Normal Approximation to the Binomial Distribution
  • Confidence Interval Theory
  • Hypothesis Testing, z and t Test for a Mean
  • Testing the Difference Between Two Means/Para
  • Test for Goodness Fit
  • Test Using Contingency Tables
  • ANOVA
  • Correlation
  • Regression
  • Coefficient of Determination

Readings

  • Required: Math 2310 Winter 2025 Bluman, Allan G. Elementary statistics: A step by step approach. 11th Edition. McGraw-Hill, 2023. The
  • (http://youtu.be/JA8cckMbVDk) ↗
    Source-linked resource
Fall 2019

Topics

  • and events, elementary probability, descriptive statistics using tables and charts, measures of central
  • tendency, variability and association, basic discrete and continuous distributions, sampling distributions
  • hypothesis testing and confidence intervals, simple linear regression and correlation, etc. Basically we
  • Successful students of this course
  • Understand the basic concepts and terminologies used in probability and statistics
  • the type of data
  • Summarize the data using charts and tables and interpret the findings
  • Calculate the measures of central tendency, variability, and association
  • Understand some basic concept in probability such as sample space and event, event operations
  • conditional probability
  • Understand the concept of independent events and to apply our understanding of independent
  • events to real-life scenarios
  • Calculation probabilities using (discrete) probability distribution tables and (continuous)
  • probabilities density functions
  • Get familiar with some discrete distributions including Binomial, Hypergeometric, Poisson, etc
  • Get familiar with some continuous distributions including normal, uniform, exponential, etc
  • Find probabilities by using the normal distribution to approximate binomial distribution
  • Central Limit Theorem
  • constructing confidence intervals

Readings

  • Statistics, 13th Edition by James T. McClave and Terry Sincich. Student’s Solution Manual (Optional) Prerequisite: MHF4U or one FCE in Mathematics Credit Weight: 0.5 (Not recognized as a mathematics credit for any Mathematics Major.)
Sources