Exercise Physiology Lab 1 HW

INDIVIDUAL DATASHEET Name: Tarek Kamal Date: 09/14/23 Tester: _____________________________________________ Time: ___________________ Fill out the following datasheet as it pertains to you, NOT your partner, unless otherwise specified. Self-Reported Data: Age: 21 (y) Sex: Male Height: 70 (in) = 177.8 (cm) Weight: 182 (lbs) = 82.7 (kg) Measured Values: Variable Trial 1 Trial 2 Trial 3 Average Height (cm) 178.5 178.4 178.5 178.45 Weight (kg) 85.4 85.5 85.9 85.6 1

LAB QUESTIONS 1. Write a clear and concise statement of whether you think a self-reported assessment of height and weight will be valid to assess measured height and weight. This should be done before you do any analysis of the class data. Provide some rationale for why you arrived at this hypothesis. This should be done in no more than 200 words (1pt). I believe that a self-reported assessment of height and weight isn’t valid to assess measure height and weight for a couple of reasons. One of those reasons is simply because people will be biased when they are reporting their data. People tend to underestimate their weight, for example. Another reason is it might have been a long time since they last measured their weight and height which would lead to an incorrect self-report. 2. Using the class data and either Excel or Google Sheets, create a table that provides a basic description of the class data. You should provide average age, height, weight, self-reported height, self-reported weight, as well as the standard deviation for the total class, males, and females. Be sure to include the number of individuals ( n ) in each group. Table 1. Averages and standard deviations for age, height, weight, self-reported height, and self- reported weight. Total (n = 11) Males (n = 6) Females (n = 6) Variables Average SD Average SD Average SD Age (y) 23.92 5.12 27 5.83 20.83 0.98 Height (cm) 171.68 8.96 178.50 6.14 164.87 5.24 Weight (kg) 78.22 15.35 87.76 12.45 68.69 12.04 SR Height (cm) 172.02 9.09 179.14 4.76 164.90 6.13 SR Weight (kg) 77.43 16.71 88.64 13.32 66.21 11.63 The formulas needed for Google Sheets are: Average: “=AVERAGE(value1:value2)” Standard Deviation: “=STDEV(value1:value2)” The formulas needed for Excel are: Average: “=AVERAGE(value1:value2)” Standard Deviation: “=STDEV.S(value1:value2)” 2

3. Using the class data and either Excel or Google Sheets, create two scatterplots: one comparing measured vs. self-reported height and one comparing measured vs. self-reported weight. Make the self-reported measures the dependent variable (y-axis) and the actual measurements the independent variable (x-axis). Be sure to include a title for the graph and label the axes. Example charts are provided below: Copy your charts below (5 points): 4

4. Using the class data and either Excel or Google Sheets, calculate a correlation coefficient for measured vs. self-reported height and for measured vs. self-reported weight using the formulas below: For Excel and Google Sheets: “=CORREL(data_y, data_x)” “data_x” corresponds to all the measured values, whereas “data_y” corresponds to all the self- reported values. An example table is provided below: Table 2. Correlation coefficients for measured and self-reported values. Measured vs SR height Measured vs SR Weight Total 0.984 0.989 Males 0.976 0.999 Females 0.975 0.969 Provide the correlation coefficients to the nearest thousandth (three decimal places) below (2 points): Measured vs SR height Measured vs SR Weight Total 0.999 0.999 Males 0.999 0.999 Females 0.999 0.999 5. Based on the correlation coefficients, are the measured and self-reported values related? Do you think that self-reported measures of height and weight are valid? Why or why not (2 points)? Based on the correlation coefficients a conclusion can be made that the values are positively correlated. I do believe that the self-reported measurements of height and weight were valid as the averaged weights and heights of the measured and self-reported measurements were very close. Even when a scatter plot was created and the liner trend line was put R^2 was close to 1. 5