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Created: Feb 9, 2017
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The New Year Weight Loss Phenomenon Survey
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Introduction


My group and I designed a survey to explore an individual's perspective of the New Year’s Weight Loss Resolution.  The focus of our survey was to determine if there is a relationship between a medical recommendation versus personal goal in losing weight for the New Year and how it may affect the individual's motivation level in pursuing this goal.  The population that was sampled were adults, with a New Year's Resolution to lose weight.  Our data was collected by asking individuals “ Do you have a New Year’s Resolution to lose weight?”, if they answered “Yes” to the question they were given a survey. Using this method we first divided the population area into two sections, those with a New Year’s Resolution to lose weight, and those who did not have a New Year’s Resolution to lose weight. With this method we used all members from the sample cluster who had a New Year’s Resolution to lose weight. We also poled through Facebook and StatCrunch.  Therefore, our survey is composed of cluster sampling and convenience sampling with voluntary responses.  



We asked the following questions:

  1. What is your personal goal weight that would make you happy? ____ (Pounds)

  2. What is your current weight? ____ (Pounds)

  3. Has a Healthcare Provider recommended to you the need to lose weight to control an actual or potential medical problem? Yes/No

  4. How motivated are you to reach your New Year’s weight loss goal? Please choose one of the following:

(5) Very Motivated

(4) Motivated

(3) Somewhat Motivated

(2) Unmotivated

(0-1) Very unmotivated

 

Data set 1. The New Year Weight Loss Phenomenon Survey   [Info]
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Looking at a Categorical Variable


The responses to the question “ How motivated are you to reach your New Year’s weight loss goal?” are shown in the pie chart below  

 

Result 1: Pie Chart for Motivational Level   [Info]
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It can be seen that half the population we surveyed is made up of individuals who are both motivated and very motivated to lose weight, 40% of the population is made up individuals who are somewhat motivated to lose weight, and the remainder 10% of the population we surveyed are both unmotivated and very unmotivated to lose weight.  


In order to see if Health Care Provider recommendation to lose weight to control an actual or potential medical problem responses differ the motivational level to reach goal weight, we can examine the bar plot below

 

Result 2: Bar Plot for Physician Recommended Weight Loss vs. Motivational Level   [Info]
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Among individuals who were recommended by a Health Care Provider to lose weight to control an actual or potential medical problem and individuals reaching a personal goal weight, the most frequent responses were from individuals who were not recommended to lose weight and are attempting to reach a personal goal.


Among individuals who were reaching a personal goal weight, about 22 people were very motivated to lose weight, about 16 were motivated to lose weight, an equal amount were unmotivated and very unmotivated to lose weight and about 29 were somewhat motivated to lose weight.


Among individuals who were recommended to lose weight by a HealthCare Provider to control an actual or potential medical problem, 5 individuals were very motivated, about 8 individuals were motivated , an equal amount were both unmotivated and very unmotivated to lose weight  and 10 individuals were somewhat motivated to lose weight.    


Looking at Numerical Variable

 

The responses to the question “ What is your current weight?” are shown in the histogram, boxplot, and summary statistics below


Result 3: Histogram of Current Weight   [Info]
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Result 4: Boxplot of Current Weight   [Info]
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Result 5: Current Weight Summary Statistics   [Info]
Summary statistics:
ColumnVariancenMeanStd. dev.Std. err.MedianRangeMinMaxQ1Q3
N21770.3933101182.3712942.0760414.1867226180212118330147205


The Histogram shows a right skewed distribution with most of the data representing current weights of 125 lbs-225 lbs.  The histogram is bimodal with the first modal representing weights of 125 lbs-150 lbs and the second modal representing weights of 175 lbs-200 lbs.   


The center of the skewed data set is best described by the median.  The median is not affected by extreme values.  The median for current weights is 180 lbs and the mean is about 183.4 lbs.  The midrange can be found by adding the minimum value and the maximum value and dividing the sum by 2. Midrange for this data is (118 lbs +330 lbs) /2, giving us a midrange value of 224 lbs.  As displayed on the histogram, the midrange for this data is not a reasonable measure of the center.  As you can note in the summary of statistics, the mean is greater than the median which is typical for a right-skewed distribution.  


There is a lot of variability in the responses to current weight.  There is a range value of 212 lbs and a standard deviation of 42.08 lbs.  The standard deviation tells us how our data is clustered around the mean.  The IQR is defined as the difference between the upper quartile ( the highest 25%) of a data set and the lower quartile (the lowest 25%) of a data set.  The upper quartile is written as Q3 and the lower quartile is written as Q1.  As shown in the summary of the statistics Q3= 205 lbs and Q1= 147 lbs.  IQR for this data set = (205 lbs- 147 lbs), giving us a value of 58 lbs for the IQR.  The Range Rule of Thumb states that the range is about 4 times the standard deviation.  Range value of this data set is 212 lbs. For this data, the range rule of thumb is not accurate, since 212 lbs / 4= 53 lbs and as stated, the standard deviation is 42.08 lbs.  The skewness of this data set and the presence of outliers makes the range/4 overestimate the standard deviation.  


The boxplot reveals a couple of outliers, which I determined by sorting the data: 300 lbs and 330 lbs.  An outlier is a point which falls more than 1.5 times the interquartile range above Q3 and below Q1.  Although these values represent weights 1.5 times the interquartile range, they are plausible because they represent weights that individuals would most likely not be willing to admit.  


Looking for a Relationship between Two Numerical Values    


To determine if there is a relationship between the responses to the questions “ What is your personal goal weight that would make you happy?” and “What is your current weight?” we looked at the scatter plot of the paired data.

 

Result 6: Scatter Plot of Goal Weight vs. Current Weight   [Info]
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The scatter plot reveals a non-linear positive trend, as one variable gets bigger, so does the other variable.  The plot reveals a constant scatter, roughly the same amount of scatter as you look across the plot.  A few outliers stand out in the scatter plot: ( 20 lbs goal weight, 181 lbs current weight) ( 165 lbs goal weight, 280 lbs current weight) ( 175 lbs goal weight, 300 lbs current weight) ( 175 lbs goal weight, 330 lbs current weight) and ( 235 lbs goal weight, 280 lbs current weight).  Outliers can dramatically affect the correlations coefficient.   


The correlation coefficient of the paired data is 0.698, as shown below

 

Result 7: Correlation between Goal Weight and Current Weight   [Info]
Correlation between N1 and N2 is:
0.69759869

 

 

Since the absolute value of r is more than 0.196, we can conclude that there is a statistically significant correlation between the individual’s personal goal weight and their current weight.  The scatter plot reveals this association between the paired variables.  

 


HTML link:
<A href="https://www.statcrunch.com/5.0/viewreport.php?reportid=66487">The New Year Weight Loss Phenomenon Survey </A>

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