everything.study
MATH 0212

Quantitative Methods for the Health Scientist

0.5 credits · Undergraduate

Spring 2026

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 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
  • – Use z-scores and percentiles to identify the position of a data value in relation to its data
  • – Be familiar with binomial distributions and compute corresponding binomial probabilities
  • – Be familiar with the normal distribution and the corresponding empirical rules
  • – Use tables to compute probabilities and z-scores associated with normal distribution

Readings

  • The required textbook package for this course is:
Fall 2025 · Quantitative Methods for the Social Scientist / Quantitative Methods for the Health Scientist

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 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
  • – Use z-scores and percentiles to identify the position of a data value in relation to its data
  • – Be familiar with binomial distributions and compute corresponding binomial probabilities
  • – Be familiar with the normal distribution and the corresponding empirical rules
  • – Use tables to compute probabilities and z-scores associated with normal distribution

Readings

  • The required textbook for this course is: ˆ Bluman: Elementary Statistics: A Brief Approach Ed: 9
Fall 2024 · Quantitative Methods for the Social Scientist / Quantitative Methods for the Health Scientist

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
  • Central Limit Theorem
  • Confidence Interval Theory
  • Hypothesis Testing, z and t Test for a Mean
  • Testing the Difference Between Two Means/Para
  • Correlation
  • Regression
  • Coefficient of Determination
  • Test for Goodness Fit
  • Test Using Contingency Tables
  • ANOVA

Readings

Fall 2023 · Quantitative Methods for the Social Scientist / Quantitative Methods for the Health Scientist

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
  • Confidence Interval Theory
  • Hypothesis Testing, z and t Test for a Mean
  • Testing the Difference Between Two Means/Para
  • Correlation
  • Regression
  • Coefficient of Determination
  • Test for Goodness Fit
  • Test Using Contingency Tables
  • ANOVA

Readings

Fall 2021 · Quantitative Methods for the Social Scientist / Quantitative Methods for the Health Scientist

Readings

  • Elementary Statistics, a step-by-step approach, by Bluman, tenth edition, McGraw-Hill.
Fall 2021 · Quantitative Methods for the Social Scientist / Quantitative Methods for the Health Scientist

Topics

  • Timing of Closures/Notification
  • / Notification
  • to close a campus or location in evening classes is being
  • the morning: considered, this
  • mentioned in the message
  • College closes a campus(s) in 9:30 a.m. By 10:00 a.m. Only affects classes
  • open by 12:00 noon later
  • past 12:00 noon
  • evening classes which
  • commence at 5 p.m. or later
  • for evening classes
  • Notification
  • Georgian social media (Facebook, Twitter)
  • Georgian website (homepage)
  • Recorded message when you call into Barrie campus at
  • Student or employee portal
  • Radio and television announcements through local and regional media

Readings

  • Required: - Introductory Statistics, by Douglas Shafer and Zhiyi Zhang.
  • Required: Descriptions of Course Components
Spring 2021

Topics

  • course students
  • calculate measures of central
  • tendency and variation for data sets and distributions
  • expected values
  • make predictions using the normal distribution
  • construct and utilize
  • confidence intervals
  • perform hypothesis tests and draw appropriate conclusions
  • describe
  • relationships between variables using correlation coefficients and regression lines
  • compare two or more population means using one way Analysis of Variance

Readings

  • Elementary Statistics: A Brief Version, 8th Edition, by A. G. Bluman.
2019–2020 · Quantitative Methods for the Social Scientist / Quantitative Methods for the Health Scientist

Readings

  • Elementary Statistics, a step-by-step approach, by Bluman, tenth edition, McGraw-Hill.
Fall 2019

Topics

  • course students
  • calculate measures of central
  • tendency and variation for data sets and distributions
  • expected values
  • make predictions using the normal distribution
  • construct and utilize
  • confidence intervals
  • perform hypothesis tests and draw appropriate conclusions
  • describe
  • relationships between variables using correlation coefficients and regression lines
  • compare two or more population means using one way Analysis of Variance
  • given during lab time (see “Bonus Marks”)

Readings

  • Elementary Statistics: A Brief Version, 8th Edition, by A. G. Bluman.
Fall 2018

Topics

  • course students
  • central tendency and variation for data sets and distributions
  • compute basic probabilities
  • and expected values
  • make predictions using the normal distribution
  • construct and utilize
  • confidence intervals
  • perform hypothesis testing and draw appropriate conclusions
  • relationships between variables using correlation coefficients and regression
  • lines
  • use the chi-square distribution to analyze sample data
  • and compare two or more
  • population means using one way Analysis of Variance
  • given during lab time (see “Bonus Marks”)

Readings

  • Elementary Statistics: A Brief Version, 8th Edition, by A. G. Bluman.
Fall 2017

Readings

  • Elementary Statistics: A Brief Version, 7th Edition, by A. G. Bluman.
Sources