battery
B-Experimental design and R intro
C-Graphical-representations
D-Numerical desctriptions of data
E-Probability
F-Discrete Probability Distribution
G-Continuous Probability Distributions
H-One Sample Inference Intro
introductory-statistics-export
I-One Sample Inference
J-Confidence Intervals
K-Two Sample Inference
L-Regression and Correlation
Guided Lecture Notes for Statistics Using Technology - Kozak
Overview
This resource is a series of guided lecture notes which cover topics from Statistics Using Technology 3rd edition, Kozak.
These notes may be used in a lecture to follow along with Statistics Using Technology 3rd edition, Kozak.
If you would like a copy of the notes completed, please reach out to Mike Rozinski at mrozinski@mohave.edu
Chapter 1 – Statistics Foundations
Material Description
This resource is a series of guided lecture notes which cover topics from chapter 1 of Statistics Using Technology 3rd edition, Kozak. Topics covered are
Competency:
Evaluate experimental design for appropriate use or misuse of statistical concepts.
Objectives:
- Define various statistical symbols and terminology
- Identify the difference between descriptive and inferential statistics
- Determine the level of measurement for a given data set
- Distinguish between parameters and statistics
- Distinguish between discrete and continuous data
- Distinguish among different types of observational studies and experiments
- Determine the sampling technique used to collect data
- Evaluate whether a sample is likely to be representative of the population
- Develop alternative conclusions to given statistical results
- Evaluate given scenarios for misuses of statistical concepts.
Context for sharing:
These notes may be used in a lecture to follow along with Statistics Using Technology 3rd edition, Kozak.
Additional information about the resource:
If you would like a copy of the notes completed, please reach out to Mike Rozinski at mrozinski@mohave.edu.
Other sections under construction.
Chapter 2 – Graphical Descriptions of Data
Material Description
This resource is a series of guided lecture notes which cover topics from chapter 2 of Statistics Using Technology 3rd edition, Kozak. Topics covered are
Competency:
Create graphical and numerical summaries of statistical data identifying descriptive characteristics (center, variation, distribution, position, trends)
Objectives:
- Construct various frequency distributions for data sets, including grouped, ungrouped, relative frequency, cumulative frequency distributions
- Construct various graphical representations of data sets, including bar graphs, histograms, stem and leaf plots, and pie charts
- Analyze frequency distributions of data sets for descriptive characteristics in context (center, variation, distribution, position, trends)
- Analyze graphical representations of data sets for descriptive characteristics in context (center, variation, distribution, position, trends)
Context for sharing:
These notes may be used in a lecture to follow along with Statistics Using Technology 3rd edition, Kozak.
Additional information about the resource:
If you would like a copy of the notes completed, please reach out to Mike Rozinski at mrozinski@mohave.edu.
Other sections under construction.
Chapter 3 – Numerical Descriptions of Data
Material Description
This resource is a series of guided lecture notes which cover topics from chapter 3 of Statistics Using Technology 3rd edition, Kozak. Topics covered are
Competency:
Create graphical and numerical summaries of statistical data identifying descriptive characteristics (center, variation, distribution, position, trends)
Objectives:
- Calculate measures of central tendency for data sets, including mean, mode, median
- Calculate measures of variation for data sets, including range, variance, standard deviation
- Calculate measures of position for data sets, including z-scores, quartiles, percentiles
- Analyze numerical measures of data sets (central tendency, variation, position) for descriptive characteristics in context (center, variation, distribution, position, trends)
- Apply numerical measures to distinguish between values that are usual and unusual
- Compare data values using measures of position
- Construct box and whisker plots as a graphical representation of data sets
Context for sharing:
These notes may be used in a lecture to follow along with Statistics Using Technology 3rd edition, Kozak.
Additional information about the resource:
If you would like a copy of the notes completed, please reach out to Mike Rozinski at mrozinski@mohave.edu.
Other sections under construction.
Chapter 4 – Probability
Material Description
This resource is a series of guided lecture notes which cover topics from chapter 4 of Statistics Using Technology 3rd edition, Kozak. Topics covered are
Competency:
Evaluate the likelihood of an event using calculated probability values.
Objectives:
- Calculate empirical probabilities of simple events using relative frequency
- Calculate theoretical probabilities of simple events
- Calculate the probability of the complement of an event
- Calculate the probability of compound events choosing the correct multiplication or addition rule
- Calculate the probability of compound events adjusting computations for dependent and/or conditional events
- Apply probabilities to distinguish between values that are usual and unusual
Context for sharing:
These notes may be used in a lecture to follow along with Statistics Using Technology 3rd edition, Kozak.
Additional information about the resource:
If you would like a copy of the notes completed, please reach out to Mike Rozinski at mrozinski@mohave.edu.
Other sections under construction.
Chapter 5 – Discrete Probability Distribution
Material Description
This resource is a series of guided lecture notes which cover topics from chapter 5 of Statistics Using Technology 3rd edition, Kozak. Topics covered are
Competency:
Create discrete probability distributions to compare theoretical probabilities to actual results.
Objectives:
- Define a random variable
- Distinguish between discrete and continuous random variables
- Determine if a distribution of a variable represents a probability distribution
- Determine whether a given procedure results in a binomial distribution
- Calculate the mean, variance and standard deviation for a probability distribution
- Construct a probability histogram from a probability distribution
- Calculate probabilities using the binomial probability formula
- Apply probabilities to determine if an unusually high or low number of successes exists among n trials
Context for sharing:
These notes may be used in a lecture to follow along with Statistics Using Technology 3rd edition, Kozak.
Additional information about the resource:
If you would like a copy of the notes completed, please reach out to Mike Rozinski at mrozinski@mohave.edu.
Other sections under construction.
Chapter 6 – Continuous Probability Distribution
Material Description
This resource is a series of guided lecture notes which cover topics from chapter 6 of Statistics Using Technology 3rd edition, Kozak. Topics covered are
Competency:
Formulate probabilities for continuous random variables using the standard normal distribution.
Objectives:
- Distinguish between discrete and continuous random variables
- Calculate the z-score for an event
- Apply the standard normal distribution to determine the probability of an event
- Construct and interpret sampling distributions for various statistics (mean, median, range, variance, standard deviation, proportion)
- Determine which statistics reasonably estimate population parameters
- Apply the Central Limit Theorem to determine probabilities of events
- Apply the rare event rule to interpret probability calculations from the Central Limit Theorem
- Approximate binomial probability distributions using the normal distribution
- Apply the continuity correction when using the normal distribution to approximate binomial probability
- Evaluate whether sample data appear to come from a population that is normally distributed using quantile plots
Context for sharing:
These notes may be used in a lecture to follow along with Statistics Using Technology 3rd edition, Kozak.
Additional information about the resource:
If you would like a copy of the notes completed, please reach out to Mike Rozinski at mrozinski@mohave.edu.
Other sections under construction.
Chapter 7 – One-Sample Inference
Material Description
This resource is a series of guided lecture notes which cover topics from chapter 7 of Statistics Using Technology 3rd edition, Kozak. Topics covered are
Competency:
Test hypotheses or claims about a population proportion, mean, and standard deviation (of variance) based on sample data.
Objectives:
- Formulate null and alternative hypotheses from a given problem statement and/or data set
- Distinguish between Type I and Type II errors
- Relate Type I error to the level of significance for a hypothesis test
- Determine which type of test (two-tailed, left-tailed, and right-tailed) is appropriate for a hypothesis test
- Decide which type of distribution is appropriate for a hypothesis test
- Test hypotheses on proportion and mean using the traditional method and P-value method
- Assess the results of hypothesis tests in context
Context for sharing:
These notes may be used in a lecture to follow along with Statistics Using Technology 3rd edition, Kozak.
Additional information about the resource:
If you would like a copy of the notes completed, please reach out to Mike Rozinski at mrozinski@mohave.edu.
Other sections under construction.
Chapter 8 – Estimation
Material Description
This resource is a series of guided lecture notes which cover topics from chapter 8 of Statistics Using Technology 3rd edition, Kozak. Topics covered are
Competency:
Formulate population parameter estimates for proportion, mean, and variance from sample data.
Objectives:
- Calculate point estimates for the proportion and mean
- Outline the disadvantages of using a point estimate for population parameters
- Determine whether the normal or t- distribution applies to the given circumstances
- Calculate margin of error for proportion and mean estimates
- Create confidence intervals (interval estimates) for proportion and mean
- Examine the meaning of a confidence interval in context
- Apply confidence intervals to determine rare events
- Test hypotheses on proportion and mean using the confidence interval method
Context for sharing:
These notes may be used in a lecture to follow along with Statistics Using Technology 3rd edition, Kozak.
Additional information about the resource:
If you would like a copy of the notes completed, please reach out to Mike Rozinski at mrozinski@mohave.edu.
Other sections under construction.
Chapter 9 – Two-Sample Inference
Material Description
This resource is a series of guided lecture notes which cover topics from chapter 9 of Statistics Using Technology 3rd edition, Kozak. Topics covered are
Competency:
Test hypotheses or claims about population parameters comparing two sets of sample data.
Objectives:
- Conduct a formal hypothesis test of a claim made about two population proportions
- Construct a confidence interval estimate of the difference between two population proportions.
- Distinguish between a situation involving two independent samples and a situation involving two samples that are not independent
- Conduct a formal hypothesis test of a claim made about two means from independent populations
- Construct a confidence interval estimate of the difference between two population means
- Determine if sample data consists of matched pairs
- Conduct a formal hypothesis test of a claim made about the mean of the differences between matched pairs
- Construct a confidence interval estimate of the mean difference between matched pairs
Context for sharing:
These notes may be used in a lecture to follow along with Statistics Using Technology 3rd edition, Kozak.
Additional information about the resource:
If you would like a copy of the notes completed, please reach out to Mike Rozinski at mrozinski@mohave.edu.
Other sections under construction.
Chapter 10 – Regression and Correlation
Material Description
This resource is a series of guided lecture notes which cover topics from chapter 10 of Statistics Using Technology 3rd edition, Kozak. Topics covered are
Competency:
Draw conclusions about relationships between bivariate sample data, making predictions if appropriate.
Objectives:
- Calculate the linear correlation coefficient for two paired variables
- Determine whether there is a statistically significant relationship between two paired variables
- Generalize the relationship between two variables with a regression equation
- Apply regression equations to predict values for the variables
- Evaluate the accuracy of predicted values using prediction intervals and the coefficient of determination
Context for sharing:
These notes may be used in a lecture to follow along with Statistics Using Technology 3rd edition, Kozak.
Additional information about the resource:
If you would like a copy of the notes completed, please reach out to Mike Rozinski at mrozinski@mohave.edu.
Other sections under construction.
LMS and Homework Materials
A Canvas course shell has been created for this material, which includes weekly discussion post assignments, weekly homework assignments, two midterm exams, and one final exam. See attached file for Canvas export package.
Some homework assignments are hosted in MyOpenMath (OER). The MyOpenMath course shell ID is 180282 and is titled Intro Statistics - Teaching w/ Technology. You are free to templete, remix, and reuse the course shell.