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Time Commuting Data Analysis

   

Added on  2019-09-20

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Module 1Data Collection ProjectThe activity that I have considered for the collection of the data for this assessment is the time it takes me to arrive to my work every day. There are two types of variable that I am likely to encounter every day, namely, dependent variable and independent variable. The dependent variable in my case is the time. I have considered the time as the dependent variable as there are likely to be multiple factors that will impact my commuting from my home to work. The time I started counting on begins from the moment I leave my outside door. After that, whatever time I spend is to be counted as the time consumed in reaching the destination. There are various independent factors that are impacting the amount of time I spend when I commute such as the traffic, construction, someone known I met on the way, and other things. Prior to the collection of the data, I developed a hypothesis that the data collect would form the bell curve. The reason behind that will be my early arrival on someday due to no traffic and roadblocks at all, and someday I may arrive very late due to number of hurdles. However, it was found that the data collected for the ten days has not formed the proper bell curve. It shows right skewed. The reason was that I spent longer duration on road for seven days from total ten days measured. The reason was that the construction was going on the route I daily take for commuting and out of ten days seven days were really disturbing. Here, it can be stated that the construction is not a usual activity and it might be possible that I could have taken less time in general. However, it does not matter how much time I spent, the point is that whether I reached the destination on time.
Time Commuting Data Analysis_1

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