Канал: Matthew Russell

Topic 21.1: Future UMN classes in statistics

Topic 21.1: Future UMN classes in statistics

Fun with birthdays

Fun with birthdays

How to use the ifelse() function in R

How to use the ifelse() function in R

Lecture 1.1 Course overview

Lecture 1.1 Course overview

Topic 21.1: Future UMN classes in statistics

Topic 21.1: Future UMN classes in statistics

Fitting Poisson and zero-inflated Poisson models

Fitting Poisson and zero-inflated Poisson models

Topic 20.2: Zero-inflated models

Topic 20.2: Zero-inflated models

Topic 20.1: Count data and distributions

Topic 20.1: Count data and distributions

Topic 19.2: Logistic regression

Topic 19.2: Logistic regression

Topic 19.1: Introduction to generalized linear models

Topic 19.1: Introduction to generalized linear models

Topic 17.1: Introduction to analysis of covariance

Topic 17.1: Introduction to analysis of covariance

Topic 17.2: Testing equality of slopes in analysis of covariance

Topic 17.2: Testing equality of slopes in analysis of covariance

Topic 17.3: ANCOVA hypothesis tests and outcomes

Topic 17.3: ANCOVA hypothesis tests and outcomes

Analysis of covariance in R

Analysis of covariance in R

Testing for equal slopes in an analysis of covariance

Testing for equal slopes in an analysis of covariance

Predicting tree height with linear mixed models and lme4

Predicting tree height with linear mixed models and lme4

ANOVA and plotting error bars in ggplot()

ANOVA and plotting error bars in ggplot()

Multiple comparison procedures in R

Multiple comparison procedures in R

Topic 16.3: Two-way analysis of variance

Topic 16.3: Two-way analysis of variance

Topic 16.2: Multiple comparisons

Topic 16.2: Multiple comparisons

Topic 16.1: Experiment-wise error rate

Topic 16.1: Experiment-wise error rate

Analysis of variance in R

Analysis of variance in R

NR 5021: ANOVA and plotting error bars

NR 5021: ANOVA and plotting error bars

Topic 15.3: Assumptions and significance in ANOVA

Topic 15.3: Assumptions and significance in ANOVA

Topic 15.2: ANOVA in action

Topic 15.2: ANOVA in action

Topic 15.1: Introduction to ANOVA

Topic 15.1: Introduction to ANOVA

Topic 18.3: Questions you should have about mixed models

Topic 18.3: Questions you should have about mixed models

Topic 18.2: Case study: Predicting tree height with mixed models

Topic 18.2: Case study: Predicting tree height with mixed models

Topic 18.1: An introduction to linear mixed models

Topic 18.1: An introduction to linear mixed models

Bugs and forest management: Integrating forest health and silviculture

Bugs and forest management: Integrating forest health and silviculture

Calculating a correlation coefficient in R

Calculating a correlation coefficient in R

Topic 14.4: How to work with lots of variables in multiple linear regression

Topic 14.4: How to work with lots of variables in multiple linear regression

Topic 14.3: An ANOVA approach to multiple linear regression

Topic 14.3: An ANOVA approach to multiple linear regression

Topic 14.2: Least squares estimates in multiple linear regression

Topic 14.2: Least squares estimates in multiple linear regression

Topic 14.1: Introduction to multiple linear regression

Topic 14.1: Introduction to multiple linear regression

Topic 13.3: How to spot bad assumptions in regression

Topic 13.3: How to spot bad assumptions in regression

Topic 13.2: Diagnostic plots of residuals

Topic 13.2: Diagnostic plots of residuals

Topic 13.1: Assumptions of regression

Topic 13.1: Assumptions of regression

Hypothesis test for the slope and intercept

Hypothesis test for the slope and intercept

Diagnostic plots for the chicken-lysine regression

Diagnostic plots for the chicken-lysine regression

One-sample t-tests in R

One-sample t-tests in R

All subsets regression in R

All subsets regression in R

Research questions and research design

Research questions and research design

Topic 12.3: Confidence intervals and ANOVA in regression

Topic 12.3: Confidence intervals and ANOVA in regression

Regression on the chicken and lysine data in R

Regression on the chicken and lysine data in R

Topic 12.3: Coefficient of determination - R-squared

Topic 12.3: Coefficient of determination - R-squared

Topic 12.2: Inference in regression: a case study with chicken-lysine

Topic 12.2: Inference in regression: a case study with chicken-lysine

Topic 12.1: Inference in regression

Topic 12.1: Inference in regression

Topic 11.3: Making predictions from regression equations

Topic 11.3: Making predictions from regression equations

Topic 11.2: Correlation and least squares regression

Topic 11.2: Correlation and least squares regression

Interpolating farmer yields

Interpolating farmer yields

Topic 11.1: Introduction to regression

Topic 11.1: Introduction to regression

Converting between Fahrenheit and Celsius - a regression approach

Converting between Fahrenheit and Celsius - a regression approach

Does human activity contribute to climate change? Determining differences by political leaning

Does human activity contribute to climate change? Determining differences by political leaning

Topic 10.2: The chi-square test for two-way tables

Topic 10.2: The chi-square test for two-way tables

Topic 10.1: Two-way tables

Topic 10.1: Two-way tables

Topic 9.4: Two-sample hypothesis tests for proportions

Topic 9.4: Two-sample hypothesis tests for proportions

Do the majority of Minnesota farmers support a nitrogen fertilizer rule?

Do the majority of Minnesota farmers support a nitrogen fertilizer rule?

How many Minnesota farmers to sample about nitrogen fertilizer rule?

How many Minnesota farmers to sample about nitrogen fertilizer rule?

Topic 9.3: Sampling distribution and hypothesis test for a proportion

Topic 9.3: Sampling distribution and hypothesis test for a proportion

Determining support for mining in Minnesota

Determining support for mining in Minnesota

Topic 9.2: Normal approximation to a binomial distribution

Topic 9.2: Normal approximation to a binomial distribution

The hazardous waste mean and variance

The hazardous waste mean and variance

The hazardous waste probability

The hazardous waste probability

Topic 9.1: The Bernoulli and binomial distribution

Topic 9.1: The Bernoulli and binomial distribution

Performing a t-test for equal variances

Performing a t-test for equal variances

Performing a t-test for unequal variances

Performing a t-test for unequal variances

Topic 8.3: F-test for variances

Topic 8.3: F-test for variances

Topic 8.2: Two sample t-test, equal variances

Topic 8.2: Two sample t-test, equal variances

Topic 8.1: Two sample t-tests, unequal variance

Topic 8.1: Two sample t-tests, unequal variance

Performing an F-test for variance differences

Performing an F-test for variance differences

Performing a one sample t test for loon eggs

Performing a one sample t test for loon eggs

Calculating a confidence interval for the loon egg

Calculating a confidence interval for the loon egg

Ethics and research: (some of) what you need to know

Ethics and research: (some of) what you need to know

How to determine sample size in R

How to determine sample size in R

How to read the t table

How to read the t table

Lecture 7.1: Power and sample size

Lecture 7.1: Power and sample size

Lecture 6.4: Paired t-tests

Lecture 6.4: Paired t-tests

Lecture 6.3: Hypothesis test for the loon data

Lecture 6.3: Hypothesis test for the loon data

Lecture 6.2: The Student's t-distribution

Lecture 6.2: The Student's t-distribution

Topic 6.1: Statistical inference

Topic 6.1: Statistical inference

Reading in a .csv file into R

Reading in a .csv file into R

Making a data frame in R

Making a data frame in R

Referencing variables in an R data frame

Referencing variables in an R data frame

Calculating the oak tree probability

Calculating the oak tree probability

Lecture 5.1: Sampling distribution of a sample mean

Lecture 5.1: Sampling distribution of a sample mean

Lecture 4.2: The five rules of probability

Lecture 4.2: The five rules of probability

Lecture 4.1: The role of probability

Lecture 4.1: The role of probability

Calculating the warbler mean and standard deviation

Calculating the warbler mean and standard deviation

Calculating the warbler standard error

Calculating the warbler standard error

Calculating the wheat yield

Calculating the wheat yield

How to read a z-table

How to read a z-table

Lecture 3.5: Continuous random variables and the normal distribution

Lecture 3.5: Continuous random variables and the normal distribution

Lecture 3.4: Central limit theorem

Lecture 3.4: Central limit theorem

Lecture 3.3: Sampling distribution of a mean

Lecture 3.3: Sampling distribution of a mean

Lecture 3.2: Random variables

Lecture 3.2: Random variables

Lecture 3.1: Measures of central tendency and spread

Lecture 3.1: Measures of central tendency and spread

Lecture 2.2: Visualizing data

Lecture 2.2: Visualizing data

Lecture 2.1: Components of data

Lecture 2.1: Components of data

Introduction to R Markdown script (corn dataset)

Introduction to R Markdown script (corn dataset)

Introduction to R script (corn dataset)

Introduction to R script (corn dataset)

Lecture 1.3: R and RStudio

Lecture 1.3: R and RStudio

Lecture 1.2: A primer on statistics

Lecture 1.2: A primer on statistics

Lecture 1.1 Course overview

Lecture 1.1 Course overview

Installing R and RStudio

Installing R and RStudio

Where will the ash wood go? Forest industry perspectives on ash wood utilization

Where will the ash wood go? Forest industry perspectives on ash wood utilization

What You Need to Know about Vector-borne Diseases in Minnesota

What You Need to Know about Vector-borne Diseases in Minnesota