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Linkedin Complete Guide to R Wrangling Visualizing and Modeling

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Files:

1. Make your data make sense.mp4 4.3 MB
2. Using the exercise files.mp4 1.7 MB
1. Comparing proportions.mp4 24.3 MB
2. Comparing one mean to a population- One-sample t-test.mp4 16.1 MB
3. Comparing paired means- Paired samples t-test.mp4 23.2 MB
4. Comparing two means- Independent samples t-test.mp4 21.0 MB
5. Comparing multiple means- One-factor analysis of variance.mp4 29.9 MB
6. Comparing means with multiple categorical predictors- Factorial analysis of variance.mp4 21.8 MB
1. Predicting outcomes with linear regression.mp4 27.7 MB
2. Predicting outcomes with lasso regression.mp4 24.7 MB
3. Predicting outcomes with quantile regression.mp4 18.3 MB
4. Predicting outcomes with logistic regression.mp4 31.3 MB
5. Predicting outcomes with Poisson or log-linear regression.mp4 9.3 MB
6. Assessing predictions with blocked-entry models.mp4 30.6 MB
1. Grouping cases with hierarchical clustering.mp4 29.2 MB
2. Grouping cases with k-means clustering.mp4 22.9 MB
3. Classifying cases with k-nearest neighbors.mp4 30.6 MB
4. Classifying cases with decision tree analysis.mp4 24.4 MB
5. Creating ensemble models with random forest classification.mp4 24.0 MB
1. Next steps.mp4 5.7 MB
1. R in context.mp4 13.5 MB
2. Data science with R- A case study.mp4 30.6 MB
1. Installing R.mp4 5.1 MB
10. Piping commands with %%.mp4 7.9 MB
2. Environments for R.mp4 11.2 MB
3. Installing RStudio.mp4 3.3 MB
4. Navigating the RStudio environment.mp4 17.4 MB
5. Entering data.mp4 17.0 MB
6. Data types and structures.mp4 28.7 MB
7. Comments and headers.mp4 13.1 MB
8. Packages for R.mp4 17.0 MB
9. The tidyverse.mp4 9.3 MB
1. Rs built-in datasets.mp4 16.3 MB
2. Exploring sample datasets with pacman.mp4 21.3 MB
3. Importing data from a spreadsheet.mp4 18.0 MB
4. Importing XML data.mp4 19.3 MB
5. Importing JSON data.mp4 21.3 MB
6. Saving data in native R formats.mp4 19.8 MB
1. Introduction to ggplot2.mp4 14.8 MB
2. Using colors in R.mp4 16.0 MB
3. Using color palettes.mp4 26.5 MB
4. Creating bar charts.mp4 24.2 MB
5. Creating histograms.mp4 13.1 MB
6. Creating box plots.mp4 12.4 MB
7. Creating scatterplots.mp4 14.1 MB
8. Creating multiple graphs.mp4 10.0 MB
9. Creating cluster charts.mp4 25.2 MB
1. Creating tidy data.mp4 34.3 MB
10. Filtering cases and subgroups.mp4 22.0 MB
2. Using tibbles.mp4 13.3 MB
3. Using data.table.mp4 15.8 MB
4. Converting data from wide to tall and from tall to wide.mp4 11.4 MB
5. Converting data from tables to rows.mp4 14.9 MB
6. Working with dates and times.mp4 18.8 MB
7. Working with list data.mp4 14.9 MB
8. Working with XML data.mp4 17.2 MB
9. Working with categorical variables.mp4 15.5 MB
1. Recoding categorical data.mp4 23.9 MB
2. Recoding quantitative data.mp4 22.1 MB
3. Transforming outliers.mp4 21.5 MB
4. Creating scale scores by counting.mp4 14.4 MB
5. Creating scale scores by averaging.mp4 8.5 MB
1. Data science with R- A case study.mp4 57.4 MB
1. Computing frequencies.mp4 14.4 MB
2. Computing descriptive statistics.mp4 25.3 MB
3. Computing correlations.mp4 16.6 MB
4. Creating contingency tables.mp4 16.8 MB
5. Conducting a principal component analysis.mp4 37.8 MB
6. Conducting an item analysis.mp4 52.1 MB
7. Conducting a confirmatory factor analysis.mp4 18.1 MB
Ex_Files_Complete_Guide_to_R.zip 6.2 MB

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