Complete Guide to Wrangling Visualizing and Modeling Data | 0F83E8666CA3F7A58681BB5D331967F7D21B9014

Complete Guide to Wrangling Visualizing and Modeling Data

Name	Complete Guide to R Wrangling Visualizing and Modeling Data	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	1.4 GB
Total Files	71
Last Seen	2025-05-01 00:13
Hash	0F83E8666CA3F7A58681BB5D331967F7D21B9014

/1. Introduction/
1. Make your data make sense.mp4	4.5 MB
2. Using the exercise files.mp4	1.8 MB
/10. Analyzing Data/
1. Comparing proportions.mp4	25.5 MB
2. Comparing one mean to a population- One-sample t-test.mp4	16.9 MB
3. Comparing paired means- Paired samples t-test.mp4	24.4 MB
4. Comparing two means- Independent samples t-test.mp4	22.0 MB
5. Comparing multiple means- One-factor analysis of variance.mp4	31.4 MB
6. Comparing means with multiple categorical predictors- Factorial analysis of variance.mp4	22.9 MB
/11. Predicting Outcomes/
1. Predicting outcomes with linear regression.mp4	29.0 MB
2. Predicting outcomes with lasso regression.mp4	25.9 MB
3. Predicting outcomes with quantile regression.mp4	19.2 MB
4. Predicting outcomes with logistic regression.mp4	32.8 MB
5. Predicting outcomes with Poisson or log-linear regression.mp4	9.8 MB
6. Assessing predictions with blocked-entry models.mp4	32.1 MB
/12. Clustering and Classifying Cases/
1. Grouping cases with hierarchical clustering.mp4	30.6 MB
2. Grouping cases with k-means clustering.mp4	24.0 MB
3. Classifying cases with k-nearest neighbors.mp4	32.1 MB
4. Classifying cases with decision tree analysis.mp4	25.6 MB
5. Creating ensemble models with random forest classification.mp4	25.2 MB
/13. Conclusion/
1. Next steps.mp4	6.0 MB
/2. What Is R/
1. R in context.mp4	14.1 MB
2. Data science with R- A case study.mp4	32.1 MB
/3. Getting Started/
1. Installing R.mp4	5.4 MB
10. Piping commands with %%.mp4	8.3 MB
2. Environments for R.mp4	11.7 MB
3. Installing RStudio.mp4	3.5 MB
4. Navigating the RStudio environment.mp4	18.3 MB
5. Entering data.mp4	17.8 MB
6. Data types and structures.mp4	30.1 MB
7. Comments and headers.mp4	13.7 MB
8. Packages for R.mp4	17.8 MB
9. The tidyverse.mp4	9.7 MB
/4. Importing Data/
1. Rs built-in datasets.mp4	17.1 MB
2. Exploring sample datasets with pacman.mp4	22.3 MB
3. Importing data from a spreadsheet.mp4	18.8 MB
4. Importing XML data.mp4	20.2 MB
5. Importing JSON data.mp4	22.3 MB
6. Saving data in native R formats.mp4	20.8 MB
/5. Visualizing Data with ggplot2/
1. Introduction to ggplot2.mp4	15.5 MB
2. Using colors in R.mp4	16.8 MB
3. Using color palettes.mp4	27.8 MB
4. Creating bar charts.mp4	25.3 MB
5. Creating histograms.mp4	13.8 MB
6. Creating box plots.mp4	13.0 MB
7. Creating scatterplots.mp4	14.7 MB
8. Creating multiple graphs.mp4	10.5 MB
9. Creating cluster charts.mp4	26.5 MB
/6. Wrangling Data/
1. Creating tidy data.mp4	36.0 MB
10. Filtering cases and subgroups.mp4	23.1 MB
2. Using tibbles.mp4	14.0 MB
3. Using data.table.mp4	16.5 MB
4. Converting data from wide to tall and from tall to wide.mp4	11.9 MB
5. Converting data from tables to rows.mp4	15.6 MB
6. Working with dates and times.mp4	19.7 MB
7. Working with list data.mp4	15.6 MB
8. Working with XML data.mp4	18.0 MB
9. Working with categorical variables.mp4	16.2 MB
/7. Recoding Data/
1. Recoding categorical data.mp4	25.1 MB
2. Recoding quantitative data.mp4	23.2 MB
3. Transforming outliers.mp4	22.5 MB
4. Creating scale scores by counting.mp4	15.1 MB
5. Creating scale scores by averaging.mp4	9.0 MB
/8. An R for Data Science Case Study/
1. Data science with R- A case study.mp4	60.2 MB
/9. Exploring Data/
1. Computing frequencies.mp4	15.1 MB
2. Computing descriptive statistics.mp4	26.5 MB
3. Computing correlations.mp4	17.4 MB
4. Creating contingency tables.mp4	17.7 MB
5. Conducting a principal component analysis.mp4	39.6 MB
6. Conducting an item analysis.mp4	54.6 MB
7. Conducting a confirmatory factor analysis.mp4	19.0 MB
/
Ex_Files_Complete_Guide_to_R.zip	6.5 MB
Total files 71