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

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File Name
Size
!! IMPORTANT Note !!.txt
287 B
!!! Please Support !!! [CoursesGhar.Com].txt
197 B
00. Websites You May Like/CoursesGhar.Com.url
114 B
00. Websites You May Like/New Internet Shortcut.url
114 B
Uploaded by [Coursesghar.com].txt
1.1 kB
Visit coursesghar.com for more awesome tutorials.url
114 B
[1] Introduction/[1] Welcome.mp4
10 MB
[1] Introduction/[1] Welcome.srt
1.9 kB
[1] Introduction/[2] What you should know.mp4
1.2 MB
[1] Introduction/[2] What you should know.srt
1.4 kB
[1] Introduction/[3] Exercise files.mp4
2.3 MB
[1] Introduction/[3] Exercise files.srt
1.4 kB
[2] 1. Ordinary Regression and Nominal Outcome Variables/[1] The normality assumption.mp4
13 MB
[2] 1. Ordinary Regression and Nominal Outcome Variables/[1] The normality assumption.srt
8.7 kB
[2] 1. Ordinary Regression and Nominal Outcome Variables/[2] Recognize abnormal distribution.mp4
12 MB
[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.mp4
11 MB
[2] 1. Ordinary Regression and Nominal Outcome Variables/[3] Forecast Too high or too low.srt
7.4 kB
[2] 1. Ordinary Regression and Nominal Outcome Variables/[4] Manage different slopes.mp4
7.8 MB
[2] 1. Ordinary Regression and Nominal Outcome Variables/[4] Manage different slopes.srt
5.2 kB
[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/[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.mp4
3.2 MB
[3] 2. Solutions to Problems with Ordinary Regression/[2] Use of odds to limit the probabilities on the upside.srt
2.1 kB
[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/[3] Logs exponents, bases, sum of logs, and the log of products.srt
5.0 kB
[3] 2. Solutions to Problems with Ordinary Regression/[4] Use of log odds to limit the probabilities on the downside.mp4
8.0 MB
[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/[5] Predict the log of the odds, the logit.mp4
12 MB
[3] 2. Solutions to Problems with Ordinary Regression/[5] Predict the log of the odds, the logit.srt
7.6 kB
[4] 3. Running a Logistic Regression in Excel/[3] Establish the log likelihood and run Solver.mp4
18 MB
[4] 3. Running a Logistic Regression in Excel/[3] Establish the log likelihood and run Solver.srt
12 kB
[4] 3. Running a Logistic Regression in Excel/[4] Interpret -2LL or deviance.mp4
14 MB
[4] 3. Running a Logistic Regression in Excel/[4] Interpret -2LL or deviance.srt
8.1 kB
[5] 4. Running a Binomial Logistic Regression in R/[1] Install the mlogit package.mp4
13 MB
[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.mp4
9.9 MB
[5] 4. Running a Binomial Logistic Regression in R/[2] Establish the data frame with XLGetRange.srt
6.3 kB
[5] 4. Running a Binomial Logistic Regression in R/[3] The mlogit function syntax.mp4
24 MB
[5] 4. Running a Binomial Logistic Regression in R/[3] The mlogit function syntax.srt
17 kB
[5] 4. Running a Binomial Logistic Regression in R/[4] Use of glm instead of mlogit.mp4
8.2 MB
[5] 4. Running a Binomial Logistic Regression in R/[4] Use of glm instead of mlogit.srt
4.5 kB
[6] 5. Running a Multinomial Logistic Regression in R/[2] Identify long versus wide data frames.mp4
16 MB
[6] 5. Running a Multinomial Logistic Regression in R/[2] Identify long versus wide data frames.srt
9.2 kB
[6] 5. Running a Multinomial Logistic Regression in R/[3] The special mlogit syntax.mp4
21 MB
[6] 5. Running a Multinomial Logistic Regression in R/[3] The special mlogit syntax.srt
13 kB
[7] Conclusion/[1] Next steps [CoursesGhar.Com].mp4
1.8 MB
[7] Conclusion/[1] Next steps [CoursesGhar.Com].srt
1.2 kB
telegram @coursesghargate.url
128 B