#### Details of this Paper

##### MAT 201 S4 Assiugnment

**Description**

solution

**Question**

Question;In this assignment;collect data for another 5?10 days with the information below. Write a paper;(1?3 pages) including all of the following content;Recalculate the mean, standard;deviation, and variance.;Is your mean increasing or;decreasing?;Explain the effects of the;larger sample size in relation to your data.;Do you think the current sample;you have is enough to draw an accurate conclusion, or do you need a larger;sample?;What conclusions can you draw;from comparing both sets of data?;Reference;material is below;Through the course of ten days we;were given an assignment. The assignment was to collect date from our daily;activities for a minimum of 10 days. For this assignment the data being;collected was the amount of time it takes me to get to the gym. There are many;variables that are identified in measuring this data. The variables in this;event, both dependent and independent can be measured and used.;The;variables that I will be using is time that it takes from the place that I;leave when going to the gym. Since this is a measurement that takes over 10;days there are two locations that are involved. Starting on a Monday the first;location is from the office. I leave from the office five days a week in a;normal work week. In that same week I leave from home two times. In this;measurement the variable is time. Leaving from the office and home are the;dependent variables. Since these are measurements of distances from different;locations. Each requires a different amount of time due to the fact they are;not the same distance from the gym. The independent variables are factors that;affect travel time to the gym. For example road conditions, accidents;construction, weather, and slow drivers.;Prior to collecting the data I had;to identify some points of reference. The starting time of 4:30 PM was the;first point I had to identify. The time it takes to get to the gym will be the;point that varies. The point from home takes me fifteen minutes to get to the;gym. The point from the office takes five minutes more. Lastly setting a point;of being late. If I arrived to the gym later than fifteen minutes from home I;considered myself late. If I arrived later than twenty minutes from the office;I was late. Depending on the independent variable this could influence the;outcome one way, or the other.;Out of the ten days and starting at;4:30 PM sharp every day I began my research. First I developed a matrix to;document the times of departure (DEP) and the times of arrival (ARR) on each of;the days. Next I included a comment section to capture the place of departure;and the conditions of travel. The time is indicated by a twenty four hour;clock. All data is as shown on the following matrix;Going to the gym;DATE: JULY;DEP;ARR;COMMENTS;7;1630;1655;Office: Traffic was slow/Monday traffic;8;1630;1650;Office: Traffic was moderate/quitting time traffic;9;1630;1650;Office: Traffic was moderate/quitting time traffic;10;1630;1650;Office: Traffic was moderate/quitting time traffic;11;1630;1705;Office: Traffic was slow/Friday traffic;12;1630;1645;Home: traffic was clear;13;1630;1645;Home: traffic was clear;14;1630;1705;Office: Traffic was slow/Monday traffic;15;1630;1650;Office: Traffic was moderate/quitting time traffic;16;1630;1650;Office: Traffic was moderate/quitting time traffic;The time is measured form the time I;start the engine (1630) to the time that I turn my engine off. In accordance to;the matrix there are 7 days that I arrived on time and three days that arrived;late during a ten day period. Ultimately the experimental probability of;arriving at the gym on time is;By;using the formula P=N/T. P represents arriving on time to the gym. The N;representing the number of times that I have arrived on time to the gym.;Finally, T representing the total of times attempted. We then come to the;conclusion of 70%, or 0.70 of the time I showed up early. The formula could;also work by switching the variable of arriving on time to arriving late. This;would give us 30%, or 0.30 times I should up late. This would still give us a;70% for the times I showed up early. The experimental probability of arriving;on time from this data set is 0.70;The;theoretical probability, being dictated by randomness, is unknown. If I were to;show up to the gym early at a 70% solution and provided that I go every day for;a three months. I would have an average rate of showing up to the gym on time.;Meaning that if I was an instructor. The students would have a 70% solution;that I would show up to class on time.;Obviously;a longer period of time collecting data, or sample size, one would have a;different outcome. The results would suggest a more accurate picture of how;many times I was on time as opposed to being late. Ultimately giving a more;accurate experimental probability of showing up at the gym on time and getting;a better result towards a theoretical probability of showing up on time.;References;Lane;D. M. (n.d.). Online Statistics Education: A multimedia course of study.;Retrieved fromhttp://onlinestatbook.com/2/index.html

Paper#60663 | Written in 18-Jul-2015

Price :*$27*