doubt regarding qualifiers exam

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Jeevana prathibha Karaka

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Nov 12, 2020, 12:18:56 AM11/12/20
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sir actually my doubt is in statistics syllabus of four weeks after each topic explained usha madam also explained how to apply it in the google sheets for example the relative frequency tables,variance,covariance mean,etc but in the hall ticket it is mentioned that goolgle sheets will not provided so is it required to watch that video  regarding what madam explained in the google sheets explanation  please clarify this doubt for me 

Jeevana prathibha Karaka

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Nov 12, 2020, 12:45:18 AM11/12/20
to Discussion forum for Statistics for Data Science I
pls clarify my doubt sir

On Thu, 12 Nov 2020 at 10:49, Jeevana prathibha Karaka <karakajeeva...@gmail.com> wrote:
sir actually my doubt is in statistics syllabus of four weeks after each topic explained usha madam also explained how to apply it in the google sheets for example the relative frequency tables,variance,covariance mean,etc but in the hall ticket it is mentioned that goolgle sheets will not provided so is it required to watch that video  regarding what madam explained in the google sheets explanation  please clarify this doubt for me 

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Nikita Kumari

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Nov 12, 2020, 1:31:18 AM11/12/20
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Hello Jeevana Pratibha,

There will not be any question in the qualifier exam from the google sheet. Also, you are not allowed to use google sheet for any type of calculations during the exam. You can watch the lectures for your understanding on how to use the google sheet but it won't come in exam.

Thanks
Nikita
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akash shrivastava

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Nov 12, 2020, 3:12:55 AM11/12/20
to Nikita Kumari, Discussion forum for Statistics for Data Science I, Jeevana prathibha Karaka
I have doubt if in question there is only mentioned variances we should consider population variance or samples variance ...
And can you tell us why n- 1 is consider in sample variance ?

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Malabika Guha Mustafi

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Nov 12, 2020, 3:27:19 AM11/12/20
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The reason n-1 is used is because that is the number of degrees of freedom in the sample. The sum of each value in a sample minus the mean must equal 0, so if you know what all the values except one are, you can calculate the value of the final one.
It will cover after sometimes , as professor said. So , for the time being sample variance should be divided by n-1.
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