LinkedIn Learning - Logistic Regression in R and Excel [CoursesGhar]

Creation Time	Sept. 19, 2023, 7:55 p.m.
Last Access Time	Aug. 7, 2024, 1:01 p.m.
File Size	220.8 MB
Keywords	and Learning Excel - LinkedIn R Logistic in Regression CoursesGhar
Total Requests	16
Total Files	49
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[5] 4. Running a Binomial Logistic Regression in R/[3] The mlogit function syntax.mp4 24.4 MB
[6] 5. Running a Multinomial Logistic Regression in R/[3] The special mlogit syntax.mp4 20.6 MB
[4] 3. Running a Logistic Regression in Excel/[3] Establish the log likelihood and run Solver.mp4 18.4 MB
[6] 5. Running a Multinomial Logistic Regression in R/[2] Identify long versus wide data frames.mp4 16.4 MB
[4] 3. Running a Logistic Regression in Excel/[4] Interpret -2LL or deviance.mp4 13.7 MB
[2] 1. Ordinary Regression and Nominal Outcome Variables/[1] The normality assumption.mp4 12.8 MB
[5] 4. Running a Binomial Logistic Regression in R/[1] Install the mlogit package.mp4 12.8 MB
[3] 2. Solutions to Problems with Ordinary Regression/[5] Predict the log of the odds, the logit.mp4 12.3 MB
[2] 1. Ordinary Regression and Nominal Outcome Variables/[2] Recognize abnormal distribution.mp4 12.0 MB
[2] 1. Ordinary Regression and Nominal Outcome Variables/[3] Forecast Too high or too low.mp4 10.6 MB
[1] Introduction/[1] Welcome.mp4 10.0 MB
[5] 4. Running a Binomial Logistic Regression in R/[2] Establish the data frame with XLGetRange.mp4 9.9 MB
[5] 4. Running a Binomial Logistic Regression in R/[4] Use of glm instead of mlogit.mp4 8.2 MB
[3] 2. Solutions to Problems with Ordinary Regression/[3] Logs exponents, bases, sum of logs, and the log of products.mp4 8.1 MB
[3] 2. Solutions to Problems with Ordinary Regression/[4] Use of log odds to limit the probabilities on the downside.mp4 8.0 MB
[2] 1. Ordinary Regression and Nominal Outcome Variables/[4] Manage different slopes.mp4 7.8 MB
[3] 2. Solutions to Problems with Ordinary Regression/[1] Use of odds instead of probabilities.mp4 6.3 MB
[3] 2. Solutions to Problems with Ordinary Regression/[2] Use of odds to limit the probabilities on the upside.mp4 3.2 MB
[1] Introduction/[3] Exercise files.mp4 2.3 MB
[7] Conclusion/[1] Next steps [CoursesGhar.Com].mp4 1.8 MB
[1] Introduction/[2] What you should know.mp4 1.2 MB
[5] 4. Running a Binomial Logistic Regression in R/[3] The mlogit function syntax.srt 17.3 KB
[6] 5. Running a Multinomial Logistic Regression in R/[3] The special mlogit syntax.srt 13.3 KB
[4] 3. Running a Logistic Regression in Excel/[3] Establish the log likelihood and run Solver.srt 11.5 KB
[6] 5. Running a Multinomial Logistic Regression in R/[2] Identify long versus wide data frames.srt 9.2 KB
[2] 1. Ordinary Regression and Nominal Outcome Variables/[1] The normality assumption.srt 8.7 KB
[4] 3. Running a Logistic Regression in Excel/[4] Interpret -2LL or deviance.srt 8.1 KB
[3] 2. Solutions to Problems with Ordinary Regression/[5] Predict the log of the odds, the logit.srt 7.6 KB
[2] 1. Ordinary Regression and Nominal Outcome Variables/[2] Recognize abnormal distribution.srt 7.6 KB
[2] 1. Ordinary Regression and Nominal Outcome Variables/[3] Forecast Too high or too low.srt 7.4 KB
[5] 4. Running a Binomial Logistic Regression in R/[1] Install the mlogit package.srt 7.1 KB
[5] 4. Running a Binomial Logistic Regression in R/[2] Establish the data frame with XLGetRange.srt 6.3 KB
[2] 1. Ordinary Regression and Nominal Outcome Variables/[4] Manage different slopes.srt 5.2 KB
[3] 2. Solutions to Problems with Ordinary Regression/[4] Use of log odds to limit the probabilities on the downside.srt 5.2 KB
[3] 2. Solutions to Problems with Ordinary Regression/[3] Logs exponents, bases, sum of logs, and the log of products.srt 5.0 KB
[5] 4. Running a Binomial Logistic Regression in R/[4] Use of glm instead of mlogit.srt 4.5 KB
[3] 2. Solutions to Problems with Ordinary Regression/[1] Use of odds instead of probabilities.srt 4.3 KB
[3] 2. Solutions to Problems with Ordinary Regression/[2] Use of odds to limit the probabilities on the upside.srt 2.1 KB
[1] Introduction/[1] Welcome.srt 1.9 KB
[1] Introduction/[3] Exercise files.srt 1.4 KB
[1] Introduction/[2] What you should know.srt 1.4 KB
[7] Conclusion/[1] Next steps [CoursesGhar.Com].srt 1.2 KB
Uploaded by [Coursesghar.com].txt 1.1 KB
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LinkedIn Learning - Logistic Regression in R and Excel [CoursesGhar]

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