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Owner: jenineh
Created: Feb 14, 2015
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Views: 1054
Tags: Changes, in, Life
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Travel and life changes
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The purpose of this survey was to collect data to see if there was any correlation with US states lived in, US states visited, and the willingness to accept life changes in a population. The population sampled was collected by six members of a group of college students. The range of samples varied from relatives, peers, coworkers, and a total of 178 surveys were collected. Various methods of sampling such as a face book survey, telephonic interviews, and the general asking of questions was utilized. Following are the questions used:

1) How many states have you lived in?

2) How many states have you visited?

3) Do you like to travel?  Yes / No

4) How willing are you to accept change in your life?  Not willing/ willing / very willing

Result 1: How Willing are you to accept Change Pie Chart With Data   [Info]
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At a quick glance, the Pie Chart shows nearly 3/4's of the surveyed population were willing to accept changes in their lives. The chart readily shows an overwhelming positive response to the acceptance of change in lives of those surveyed, and is an easy chart to read with red and green as the most responded on colors. Approximately 9% of those surveyed were not willing to accept change, and is easily read on the Pie chart highlighted in blue. 

Result 2: relative freq Bar Plot With Data   [Info]
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This bar plot shows responses to two different questions. The first question is do you like to travel? This is shown on the bottom of the bar plot. The second question is how willing are you to accept change in your life? Responses could be willing, very willing, or not willing at all. This was not an ideal graph to show this type of comparative response as it is difficult to see or understand. One of the questions was a Yes or No response, and the other question had 3 variable responses which makes it difficult to see as glance which response is to which.

Result 3: States lived in Histogram   [Info]
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How many States have you lived in responses are shown on this Histogram. It is a unimodal, slightly skewed to the right histogram. The majority of response is seen at the left side of the graph with the number 2 being the most frequent response. I found it quite surprising that the majority of those surveyed had lived in only 2 States. The skewed portion or tail off to the right of the graph shows those respondents who have lived in 8 States or greater.

Result 4: Boxplot of Lived in States   [Info]
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The box plot shows greater than 50% of people having lived in greater than 2 states. The n which is the population is 178. The mean is 2.618, with a range of 9 and a minimum of 1. Standard deviation measures the variation of the values around the mean and its value here is 1.74. The extending whisker from the box plot stops at the last data value before any outlier. There is an outlier in this data set noted by the fencing. A number in the list that is much smaller or much larger than the rest will pull the mean in its direction causing the standard deviation to be larger. A calculation error or outlier can dramatically affect the standard deviation, but in this case it is reasonable as some of the surveyed could reasonable have lived in more than 8 different states.

Result 5: States lived in with Summary Stats   [Info]
Summary statistics:
ColumnnMeanVarianceStd. dev.Std. err.MedianRangeMinMaxQ1Q3
States Lived in1782.61797753.02837551.74022280.130435222911014


Summary statistics result here at a quick glance shows all the values. The IQR or interquartile range is Q3-Q1 which gives the spread of the middle 50% of data. The dividing line on the box plot confirms this number and indicates the range of data is 2-4 with the majority of responses in this section of the box plot. Standard deviation measures the variations of the values around the mean.

Result 6: States lived in vs States visited Scatter Plot   [Info]
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This scatter plot shows a positive trend with a great deal of scatter. Scatter plots often show a relationship between 2 variables. Visual exam confirms that the points approximate a straight line pattern which is a requirement for linear correlation. The majority of people in the study have lived in 6 or less states. A couple of lone points in the 8-10 range are from respondents who had lived in more than eight states which is not all that unusual. The scatter plots shows many people visiting a greater number of states.

Correlation coefficient- r is a number that measures how well paired sample data fit in a straight line pattern. The value of r determines that there is or is not a linear correlation. The points on the scatter plot showed an approximate straight line pattern.I found the r value of 0.147 which showed there was not statistical significance.


Result 7: States lived in vs States visited Correlation   [Info]
Correlation between States Lived in and States visited is:

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