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Hello everyone,
I have a new dataset that I have been working on and I'm doing some brainstorming. The dataset contains data on the student logins into a career development system. my raw data is not comprehensive and has only the following headers:
Student ID | Gender | Enrolment Status | Campus | Number of logins | Last login date | College |
I have done all the basic data anaylsis on this dataset like the total number of logins, average logins per student, logins by gender...etc. I'm wondering what other statistical tests or interesting data that I can obtain from this data set?
I was thinking of finding the std. dev. and variance but couldn't understnad how they would fit in this context.
I'm also interested in doing something with the last login date but I couldn't get any ideas.
Solved! Go to Solution.
Hi, @SusuYes
You can try to calculate the number of days between the last login date of each student and today to get an idea of the length of time between student logins.
If there is a field for first login time, you can also count the number of logins of new and old users in weekly dimension to understand the status of students' interest in this system.
Best Regards,
Community Support Team _Charlotte
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
Hi, @SusuYes
You can try to calculate the number of days between the last login date of each student and today to get an idea of the length of time between student logins.
If there is a field for first login time, you can also count the number of logins of new and old users in weekly dimension to understand the status of students' interest in this system.
Best Regards,
Community Support Team _Charlotte
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
How does login frequency evolve over time? What does the distribution of login look like? (Try a Pareto analysis)
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