Linear Regression in R | Linear Regression in R With Example | Data Science Algorithms | Simplilearn

Linear Regression in R | Linear Regression in R With Example | Data Science Algorithms | Simplilearn

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@anjalipriya2160
@anjalipriya2160 - 13.08.2022 23:08

This is very nice tutorial I have seen so far , really helpful . please can u share the dataset?

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@simrandubb7055
@simrandubb7055 - 02.06.2022 22:54

Hi there, could I please get access to the dataset?

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@sanikajoshi1198
@sanikajoshi1198 - 31.03.2022 19:58

Where exactly is the dataset?

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@taruneeshsachdeva1615
@taruneeshsachdeva1615 - 30.03.2022 03:27

Thank you so much for the tutorial. Can I have the dataset so I can practice on my own

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@katyhessni
@katyhessni - 09.03.2022 19:19

Hi . Thank you so much for your video
I just have a question , i tried to check linear regression assumptions for this model and by drawing the qqplot i can clearly see that the residuals are not normally distributed . How can i fix this problem ?
I also tried boxcox transformation but that didn't help .

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@sophiaplants3384
@sophiaplants3384 - 03.03.2022 10:22

where can I get the dataset?

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@praveenfrancis1899
@praveenfrancis1899 - 31.01.2022 00:28

/where is the csv file to download?

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@laurachoi9180
@laurachoi9180 - 17.01.2022 14:42

hi - brilliant video - could you please share the data set please? happy to share my email

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@feliperod7576
@feliperod7576 - 09.12.2021 23:24

super!

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@kavitakhandelwal7894
@kavitakhandelwal7894 - 19.11.2021 04:16

Please correct these errors:
correction 1: subset function = is used in the place of ==
correction2: rmse = sqrt(mean((pred - test$Revenue)^2))

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@ahmed007Jaber
@ahmed007Jaber - 21.09.2021 07:31

thank you for this. tried this one and got an error
rmse <- sqrt(mean(y_pred- set2$TotalSales)^2)
Warning message:
In y_pred - set2$TotalSales :
longer object length is not a multiple of shorter object length



if I want to do the prediction on alternate days, how would I do that????

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@pritamsaha6804
@pritamsaha6804 - 15.09.2021 06:57

give the data link

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@karankadam160
@karankadam160 - 11.07.2021 11:39

Where I will get that sales dataset you used ?

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@rasalghul641
@rasalghul641 - 27.06.2021 17:44

That's great work!
Amazing work
Where can I get the dataset from?

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@noorsyed5727
@noorsyed5727 - 27.06.2021 17:33

dataset link?

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@Bacel89
@Bacel89 - 22.06.2021 22:37

where can I find the dataset?

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@asixtray
@asixtray - 21.06.2021 06:23

Very Nice tutorial. Could you please send datasets.

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@richardschmalhofer3477
@richardschmalhofer3477 - 13.06.2021 21:25

Great explanation!! Only issue is the quality of the mic.

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@alphonceassenga9247
@alphonceassenga9247 - 14.04.2021 15:42

where can I get the sales dataset?

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@alioraji9829
@alioraji9829 - 07.04.2021 12:42

Hi there, one of the best tutorial I've ever seen for Linear Regression. I'm so interested in Dataset and I appreciate if you share it to get practice and hands-on with your video

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@jerinarul9590
@jerinarul9590 - 01.04.2021 17:52

when i try to do plot fuction using large data set i get "figure margins are too large"
what should i do then

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@abhinaytotawar1524
@abhinaytotawar1524 - 25.03.2021 13:50

Could you please share the given dataset to me on my mail id.

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@revathias4568
@revathias4568 - 19.03.2021 21:39

Very useful video.
Please provide me that dataset urgently.
Pls consider my request

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@alecdelu83
@alecdelu83 - 27.02.2021 04:12

Hi! Excellent video! can I please have the data set?

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@Johmatri
@Johmatri - 10.02.2021 16:41

what do the values for head() mean?

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@jgcornell
@jgcornell - 08.01.2021 15:58

Thanks so much, very nicely explained and demonstrated

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@priyanshup1380
@priyanshup1380 - 08.12.2020 10:38

HEY, COULD YOU PLZ GET ME THAT DATA SET!

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@shubhangisaxena7113
@shubhangisaxena7113 - 21.11.2020 16:24

Great video and easy explanation. Could I please have the dataset? ([email protected])
Thanks a lot :)

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@JarJarBinkz68
@JarJarBinkz68 - 02.11.2020 00:30

thanks a lot.

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@ricksanchez845
@ricksanchez845 - 06.10.2020 12:32

Thank you man, you made it so simple. in 3-4 hour lasting classroom lectures, i do not understand shit. However, such videos make it so simple.

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