[LinkedIn] Complete Guide to R: Wrangling, Visualizing, and Model...

  • Category Other
  • Type Tutorials
  • Language English
  • Total size 854.3 MB
  • Uploaded By SunRiseZone
  • Downloads 589
  • Last checked 1 day ago
  • Date uploaded 1 year ago
  • Seeders 20
  • Leechers 30

Infohash : 264E78459680CA3C9EA6765D2C8184FCC5853567



📝 Request a Course: 👉 docs.google.com/forms

🔗 Official Course URL: linkedin.com/learning/complete-guide-to-r-wrangling-visualizing-and-modeling-data

📘 Course Overview:
Dive into the advanced functionalities of R with Complete Guide to R: Wrangling, Visualizing, and Modeling Data . This course, led by data analytics expert Barton Poulson, provides a deep dive into the crucial techniques of data wrangling, visualization, and modeling with R. Ideal for intermediate learners looking to enhance their skills, the course offers hands-on examples and detailed instruction.

📖 What You'll Learn:
- Data Wrangling: Master the import, cleansing, and conversion of data for detailed analysis.
- Data Visualization: Create impactful visualizations like bar charts, histograms, and scatterplots.
- Data Transformation: Efficiently handle categorical, qualitative, and outlier data to meet research needs.
- Modeling Techniques: Develop and apply statistical models to interpret complex datasets.

🎯 Course Benefits:
- Expert Instruction: Learn from Barton Poulson, a seasoned expert in data analytics.
- Comprehensive Content: Gain thorough insights with 70 detailed lessons.
- Practical Experience: Engage in exercises that reinforce data manipulation and analysis skills.
- Resource Access: Utilize R and RStudio to their fullest potential with guided navigation and examples.

⏱️ Total Hours of Course: 8 hours 15 minutes

🗃️ Course Size: 854.3 MB

🔤 Subtitles: English, Persian

Who is this course for?
Ideal for those with a foundational knowledge of R programming, looking to advance in data wrangling, visualization, and modeling to enhance their analytical skills in various research or industry applications.

Files:

Complete Guide to R - Wrangling, Visualizing, and Modeling Data
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  • exercise_files Ex_Files_Complete_Guide_to_R Exercise Files
    • Complete-Guide-to-R-README.txt (1.0 KB)
    • Complete-Guide-to-R.Rproj (0.2 KB)
    • code
      • 01_02_CaseStudy.R (7.8 KB)
      • 02_04_Navigating.R (0.8 KB)
      • 02_05_EnteringData.R (1.4 KB)
      • 02_06_DataTypes.R (2.6 KB)
      • 02_07_Comments.R (1.1 KB)
      • 02_08_Packages.R (1.5 KB)
      • 02_09_Tidyverse.R (2.0 KB)
      • 03_01_BuiltInDatasets.R (1.0 KB)
      • 03_02_ExploreSampleData.R (3.3 KB)
      • 03_03_ImportSpreadsheet.R (1.4 KB)
      • 03_04_ImportXML.R (2.0 KB)
      • 03_05_ImportJSON.R (2.0 KB)
      • 03_06_SaveRData.R (2.9 KB)
      • 04_02_Colors.R (2.4 KB)
      • 04_03_Palettes.R (3.3 KB)
      • 04_04_BarCharts.R (3.2 KB)
      • 04_05_Histograms.R (2.2 KB)
      • 04_06_Boxplots.R (2.1 KB)
      • 04_07_Scatterplots.R (2.0 KB)
      • 04_08_MultipleGraphs.R (2.4 KB)
      • 04_09_ClusterCharts.R (2.0 KB)
      • 05_01_TidyData.R (4.1 KB)
      • 05_02_Tibbles.R (1.7 KB)
      • 05_03_DataTable.R (2.1 KB)
      • 05_04_ConvertWideToTall.R (1.6 KB)
      • 05_05_ConvertTableToRows.R (2.8 KB)
      • 05_06_DatesAndTimes.R (3.0 KB)
      • 05_07_ListData.R (1.7 KB)
      • 05_08_XMLData.R (2.3 KB)
      • 05_09_CategoricalVariables.R (2.4 KB)
      • 05_10_FilterCases.R (1.9 KB)
      • 06_01_RecodeCategoricalData.R (4.0 KB)
      • 06_02_RecodeQuantitativeData.R (2.4 KB)
      • 06_03_TransformOutliers.R (3.8 KB)
      • 06_04_CountScores.R (2.3 KB)
      • 06_05_AverageScores.R (1.8 KB)
      • 07_01_CaseStudy.R (8.3 KB)
      • 08_01_Frequencies.R (1.8 KB)
      • 08_02_Descriptives.R (2.2 KB)
      • 08_03_Correlations.R (2.0 KB)
      • 08_04_ContingencyTables.R (2.2 KB)
      • 08_05_PCA.R (3.1 KB)
      • 08_06_ItemAnalysis.R (5.0 KB)
      • 08_07_CFA.R (1.9 KB)
      • 09_01_Proportions.R (2.5 KB)
      • 09_02_OneSamplet.R (1.8 KB)
      • 09_03_PairedSamplest.R (3.0 KB)
      • 09_04_IndependentSamplest.R (2.7 KB)
      • 09_05_OneFactorANOVA.R (3.1 KB)
      • 09_06_FactorialANOVA.R (2.2 KB)
      • 10_01_LinearRegression.R (3.2 KB)
      • 10_02_LassoRegression.R (3.0 KB)
      • 10_03_QuantileRegression.R (2.5 KB)
      • 10_04_LogisticRegression.R (3.8 KB)
      • 10_05_PoissonRegression.R (1.9 KB)
      • 10_06_BlockedEntry.R (2.9 KB)
      • 11_01_HierarchicalClustering.R (3.1 KB)
      • 11_02_kMeansClustering.R (2.8 KB)
      • 11_03_kNN.R (2.9 KB)
      • 11_04_DecisionTrees.R (2.7 KB)
      • 11_05_RandomForests.R (3.4 KB)
      data
      • MobileDataSource.txt (0.1 KB)
      • MobileOS_US.csv (10.9 KB)
      • MobileOS_US.xlsx (21.2 KB)
      • ScaleData.xlsx (2.4 MB)
      • StateData-Code-Book.txt (3.8 KB)
      • StateData.csv (7.2 KB)
      • StateData.rdata (2.6 KB)
      • StateData.rds (0.3 KB)
      • StateData.xlsx (18.7 KB)
      • StateData2.rds (1.1 KB)
      • XMLdata.xml (286.3 KB)
      • b5-and-big5-Code-Book.txt (4.4 KB)
      • b5.csv (1.8 MB)
      • b5_df.csv (584.9 KB)
      • b5_df.rds (135.9 KB)
      • b5_df_jamovi.omv (4.1 MB)
      • big5.csv (2.2 MB)
      • winequality-red.csv (83.7 KB)
      output
      • barchart.pdf (4.4 KB)
      • barchart.png (62.1 KB)
    • 📝-Request-a-Course-👉.txt (0.3 KB)

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