GEOG380 Basic Stats with R
Welcome
Introduction
Book data collection
What is R?
Do not dispair, please
Class expectations
1. Scientific method
2. Data manipulation
3. Data display
4. Descriptive stats
5. Correlation
6. Regression
7. Hyphothesis testing
8. One sample test
9. Two sample test
10. More than two sample test
Grading
1
The scientific method
The problem
Narrow the problem
Search prior knowledge
Back to defining the problem
The hyphotesis
The null hypothesis
H0
The alternate hypothesis
H1
The experiment
Population, sample, subject
Variables
The control and treatment
Replication
Pseudo-Replication
Randomness
Design experiment
Data collection
Analyze your data
Vizualize the data
Write report
Excercises
Exercise 1
Exercise 2
Homework
2
Installing programs
Installing R
Tinn-R
R-Studio
Installing packages
Asking for help
Exercise
3
Basics on data manipulation in R
Variables
Comments
Operators
Assignment operators
Arithmetic operators
Character operators
Custom made functions
Data structure types
Vectors
Matrix
DataFrames
Loading your own data into R
Calling elements in a data frame
Filter data
Pivot table
Merge data
Subsetting columns
Deleting columns
Selecting columns
Adding results to databases
Exercise
Homework
4
Basic plots
Scatterplots
Histograms
Density plots
Plotting maps
Animated plots
Saving plots
Excersise
5
Descriptive statistics
Data distributions
Central tendency
The arithmetic mean
The trimmed mean
The weighted average
The median
The mode
Dispersion
The minimum and the maximum
The range
The percentile
The quantile
The variance
The standard deviation
The coefience of variance
Exercises
Homework
6
Correlation
Visualization of relationships
Linear relationships
Non-linear relationships
The Covariance
The Correlation Coefficient, r
Alternative formulation
Interpreting r
Causation
Significance
correlation tables
Correlation p-values
Exercises
Homework
7
Regression
Parts of a line
How to interpret the slope
How to interpret the intercept
Purpuse of the regression line
The least-squares line
Understanding the least-squares line
Deciphering the least-squares line
Estimating the least-squares line
Refreshing the Slope
The slope
The intercept
Linear regression in R
The coeficient of determination
Predict: Interpolation, Extrapolation
Interpolation and Extrapolation
Outliers
The significance
Multiple regression
Non-linear regression
Exercises
Homework
8
Hypothesis testing
Background info
p-value and alpha
Approach to testing a hyphothesis
Stating hyphotheses and tails
Accepting or rejecting the null hypothesis
Testing a hypothesis by brutal force
Error types
Exercises
Homework
9
Standard hypothesis tests
Alternative types of tests
One sample test
Two sample test
More than two sample test
Selecting the right test
Homework
10
One sample tests
The one-sample Z-test by hand
The one-sample Z-test in R
The one-sample T-test by hand
The one-sample T-test in R
Homework
11
Two sample tests
The two-sample Z-test by hand
The two-sample Z-test in R
The two-sample T-test by hand
The two-sample T-test in R
Homework
12
Multiple sample test
ANOVA reasoning
ANOVA by hand
Stating Hyphotheses
Total variance
Between group variance
Within group variance
Variance partitioning
F-Statistics
Critical F-value
Ploting the data
ANOVA in R
Post-hoc test in R
Checking assumptions
Outliers
Normality
Homogneity of variance
Homework
13
Final project
By Camilo Mora, Ph.D.
Exercise
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