Type of data: Check all that apply. Use "Other" to specify other types so that we can include them in further updates. |
number
series
table
|
Variable labels of dataset (the names of the variables) |
average step numbers(by month), time(month), distance |
Outline of data |
The data is my step numbers counted by my cell phone in a period of time (from 2019.1.15 to now). The data is produced by my cell phone(iPhone XR, iOS 12) every day as long as I take it and go for a walk.
But when I go out with my friends and walk the same distance. I realized that the number is decided by the brand of the phone in some aspects. For example, Huawei's phones running Android OS are easy to have a very high step count, while iPhone running iOS tends to have fewer count.
So the data are collected for helping cell phone factories to make the counters more accurater. |
Simulation process |
Ask one person to walk 2 km with some different brands' phones and a step counter which is absolutely accurate comparing with cell phones. Then compare the difference step numbers. Actually, as far as I'm concerned, iPhones tend to have fewer steps than Android phones, but I don't know which group is right. |
Expected outcome of the process (obtained knowledge, analysis results, output of tools) |
Obtain the explanations of these 2 questions:
1. Is iPhones' step counter more accurate or Android phones' ?
2. Is there any way to help the smartphone factories improve the accuracy? |
Anticipation for analyses/simulations other than the typical ones provided above |
Compare and analyze to create a new way to help improve the step count function in a smartphone. |
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