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## Variables and Level of Measurement

The objective is to calculate the BMI of a person and to analyze the significant difference between different gender group and age group. The priority of the research is to understand the Healthy eating and Physical activity behavior of a person. Based on calculated BMI objective is to define whether person comes under obese, normal, overweight, and underweight, and to analyze the percentage of these categories. Based on all the categories, researcher can predict the Obesity level such as obese, normal, overweight, and underweight.

Justification of Question:  Based on Variable Age, it can be identified that weight and height of a person is less, more or perfect.  Based on these variable researcher can analyze that which age group has physically active life? , and which Age group consumes more healthy Foods.

Type of variable: Age is a discrete (Technically continuous) variable.

Level/Scale of measurement: Age is a Ratio Variable because age cannot be in negative and it has true zero values.

Type of visualization: Bar Chart is a visualization technique through which count of Age group can be visualized, which age group has participated more in a survey. Scatter plot can also be used when researcher wants to compare or correlate the variable Age with other variables.

Justification of Question: Weight of person helps in calculation of BMI of a person that helps in knowing the condition of a person (obese, normal, overweight, and underweight).

Type of variable: Continuous Variable

Level/Scale of measurement: Interval Scale

Type of visualization: Bar Chart helps in identifying the unique values of weight and highest weights, Scatter plot helps in comparing weight variable with other variables, and Histogram helps in identifying whether data is normal or not.

Justification of Question: Height of person helps in calculation of BMI of a person that helps in knowing the condition of a person (obese, normal, overweight, and underweight).

Type of variable: Continuous Variable

Level/Scale of measurement: Interval Scale

Type of visualization: Bar Chart helps in identifying the unique values of height and highest weights, Scatter plot helps in comparing height variable with other variables, and Histogram helps in identifying whether data is normal or not.

A] Male B] Female C] Others

Justification of Question: Researcher can analyze the obesity percentage level among the gender group (Male, Female and other category). This will help the researcher in identifying that which gender group are more facing obesity problem or which gender group needs to follow healthy diets.

Type of variable: Categorical variable

Level/Scale of measurement: Nominal Scale

Type of visualization: Pie chart, Bar chart

Q5] How often you diet?

A] Never B] Rarely C] Sometimes D] Often E] Always

Justification of Question: This question helps the researcher in identifying after following and not following a diet in both the conditions is still person has the obesity or underweight or overweight issues. Which category (A-E) helps the person having healthy life.

Type of variable: Categorical variable

Level/Scale of measurement: Ordinal Scale

Type of visualization: Bar chart, Pie chart.

Q6] Do you live physically active life?

A] Yes B] No

## Visualization Techniques

Justification of Question: This question helps the researcher in identifying after having physically active and not physically active life in both the conditions is still person has the obesity or underweight or overweight issues. If yes then the person is seriously suffering from any disease or person does not follow healthy/nutritious diet.

Type of variable: Categorical Variable.

Level/Scale of measurement: Ordinal Scale

Type of visualization: Pie chart, and Bar chart.

Q7] Do you consume Alcohol?

A] Never B] Rarely C] Sometimes D] Often E] Always

Justification of Question: This variable helps researcher in analyzing whether Consumption of alcohol is the main cause of obesity issue or not? As well person who does not consume alcohol has normal weight?

Type of variable: Categorical variable

Level/Scale of measurement: Ordinal Scale

Type of visualization: Pie chart, and Bar chart.

Q8] Do you crave specific foods?

A] Never B] Rarely C] Sometimes D] Often E] Always

Justification of Question: This question helps the researcher in identifying a person’s control towards their favorite specific foods/meals. Researcher can identify the percentage of in a gender group or age group that has more or less specific food cravings. The level of food cravings (A-E) will help the researcher to Analyze the main cause of obesity.

Type of variable: Categorical Variable

Level/Scale of measurement: Ordinal Scale.

Type of visualization: Bar chart, and Pie chart.

Q9] How much time you give to Exercise/Yoga?

Justification of Question: This question helps the researcher in analyzing the optimum time for exercise which helps the person to have healthy life with normal weight.

Type of variable: Continuous Variable.

Level/Scale of measurement: Ratio (Because time cannot be in negative)

Type of visualization: Pie chart, Bar chart.

Q10] Do you exercise daily?

A] Yes B] No C] Sometimes

Justification of Question: This question helps the researcher that the previous two questions answered by participant is credible or not, as well as helps the researcher in identifying the percentage of doing exercise in gender groups i.e. which gender group prefer exercise more!

Type of variable: Categorical Variable

Level/Scale of measurement: Ordinal Scale

Type of visualization: Bar chart, pie chart

Q11] How many meals do you have in a day?

A] 1 B]2 C] 3 D] 4+

Justification of Question: This Question helps the researcher in identifying the root cause of obesity in person, Number of meals also responsible for the obesity level in person until it is healthy.

Type of variable: Discrete Variable

Level/Scale of measurement: Ordinal Scale

Type of visualization: Bar chart, and Pie chart.

Q12] Do you take breakfast before going to College/School/Work?

A] Never B] Rarely C] Sometimes D] Often E] Always

Justification of Question:

Type of variable: Categorical Variable

Level/Scale of measurement: Ordinal Scale

Type of visualization: Bar chart, and Pie chart

Q13] Does your school/College/Workplace promotes or motivates for the healthy diet?

A] Yes B] No

Justification of Question: This question helps the researcher in identifying the awareness level for healthy diet in the society. Will students or workers get motivation for healthy diet?

Type of variable: Categorical Variable

Level/Scale of measurement: Ordinal Scale

Type of visualization: Bar chart, and Pie chart

Q14] Does your school/College/Workplace promotes or motivates for the Exercise/Yoga?

## Gender and Obesity Analysis

A] Yes B] No

Justification of Question: This question helps the researcher in identifying the awareness level for Exercise/Yoga in the society. Will students or workers get motivation for doing Exercise/Yoga?

Type of variable: Categorical Variable (Binary)

Level/Scale of measurement: Ordinal Scale

Type of visualization: Bar chart, and Pie chart

Q15] Do you take Protein foods in your diet daily?

A] Never B] Rarely C] Sometimes D] Often E] Always

Justification of Question: This question helps the researcher in identifying the awareness level for the importance of protein in a diet among the people.

Type of variable: Categorical Variable

Level/Scale of measurement: Ordinal Scale

Type of visualization: Bar chart, and Pie chart

Q16] How many glasses of water you drink daily?

Justification of Question: This Question helps the researcher to identify the consumption of water by the people is it low, high, or normal because water also includes in healthy diet, it helps in maintaining the body fluids.

Type of variable: Discrete Variable

Level/Scale of measurement: Ratio Scale.

Type of visualization: Histogram plot, Bar chart.

Q17] Do you believe more glasses or water can keep you healthy?

A] Yes B] No

Justification of Question: This question helps the researcher in identifying the awareness level for the importance of water in a diet among the people.

Type of variable: Categorical Variable (Binary)

Level/Scale of measurement: Ordinal Scale

Type of visualization: Bar chart, and Pie chart

Q 18] How often do you eat Fruit and Vegetables?

A] Never B] Rarely C] Sometimes D] Often E] Always

Justification of Question:  This question helps the researcher in analyzing whether person is having healthy diet or not.

Type of variable: Categorical Variable

Level/Scale of measurement: Ordinal Scale

Type of visualization: Bar chart, and Pie chart

Q19] How often do you eat Fish and Meats?

A] Never B] Rarely C] Sometimes D] Often E] Always

Justification of Question: This question helps the researcher in analyzing whether person is having healthy diet or not also, helps in identifying that person is vegetarian or not?

Type of variable: Categorical Variable

Level/Scale of measurement: Ordinal Scale

Type of visualization: Bar chart, and Pie chart

Q20] How often do you eat Fast/Junk Foods?

A] Never B] Rarely C] Sometimes D] Often E] Always

Justification of Question: This question helps the researcher in analyzing the food or diet behavior of a person; it helps in identifying the researcher the level of fast food craze among the people which is the main cause of obesity.

Type of variable: Categorical Variable

Level/Scale of measurement: Ordinal Scale

Type of visualization: Bar chart, and Pie chart

Collection of Survey Data

To collect the data target population will be from the age group under 18 to 55+ which go to school, colleges, and work. School student is included in the study because today a lot of children’s are facing the obesity issue due to unhealthy diets, workers face this issues due to work load as they are not able to take care of their diet also most of the work is not related physical activity which leads to obesity problem.  Online survey and questionnaire tools are easiest way to get the primary data, but this has cons that most of the target population such as students possibly not able to get this form. So, to collect the data online and offline both survey is needed to get good amount of data and information from all the targeted population (Blom, et., al, 2020).

## Diet and Exercise Impact on Obesity

Different Sampling method exists, but in this research targeted population is from all the groups, so sampling method would be Random sampling but from these specific criteria of targeted population i.e. School, College, and Work. There is no criteria has been set to participants in the survey, anyone can participate. Representative sampling to the population needs to be collected. Target population is School student, college student, and workers. So, the appropriate method of collecting data from this target population is stratified sampling. Taherdoost, 2016 explained that in stratified sampling, Every group must have same sample size, Within the group homogeneity exists i.e. properties of population is homogenous for example, Strata 1 is about school student, Strata 2 is about College Student, and Strata 3 is about Workers; Between the group heterogeneity exists i.e. properties of population between the group is not same.

From these 3 stratums, random samples selects for the further Analysis. Formula to calculate sample size for every stratum is, (Total sample Size/Total Population)*Population of subgroup.

But this sampling method has some disadvantage; there is a high chance of biasedness presence in the data. This method is not applicable for small samples, sample size or population size both should be large. Large number of samples provide the most accurate and representative results, if results are not representative to the population then it is a indication that more samples needed for more accurate analysis (Latpate, et., al, 2021).

References

Adab, P., Barrett, T., Bhopal, R., Cade, J.E., Canaway, A., Cheng, K.K., Clarke, J., Daley, A., Deeks, J., Duda, J. and Ekelund, U., 2018. The West Midlands ActiVe lifestyle and healthy Eating in School children (WAVES) study: a cluster randomised controlled trial testing the clinical effectiveness and cost-effectiveness of a multifaceted obesity prevention intervention programme targeted at children aged 6-7 years. Health Technology Assessment (Winchester, England), 22(8), p.1.

Arnab, R., 2017. Survey sampling theory and applications. Academic Press.

Blom, A.G., Cornesse, C., Friedel, S., Krieger, U., Fikel, M., Rettig, T., Wenz, A., Juhl, S., Lehrer, R., Möhring, K. and Naumann, E., 2020, June. High frequency and high quality survey data collection. In Survey Research Methods (Vol. 14, No. 2, pp. 171-178).

Bolton, K.A., Kremer, P., Gibbs, L., Waters, E., Swinburn, B. and De Silva, A., 2017. The outcomes of health-promoting communities: being active eating well initiative—a community-based obesity prevention intervention in Victoria, Australia. International Journal of Obesity, 41(7), pp.1080-1090.

Brown, C.L. and Perrin, E.M., 2018. Obesity prevention and treatment in primary care. Academic pediatrics, 18(7), pp.736-745.

Etikan, I. and Bala, K., 2017. Sampling and sampling methods. Biometrics & Biostatistics International Journal, 5(6), p.00149.

Ghojogh, B., Nekoei, H., Ghojogh, A., Karray, F. and Crowley, M., 2020. Sampling algorithms, from survey sampling to Monte Carlo methods: Tutorial and literature review. arXiv preprint arXiv:2011.00901.

Latpate, R., Kshirsagar, J., Gupta, V.K. and Chandra, G., 2021. Advanced Sampling Methods. Springer Singapore.

Leme, A.C.B., Philippi, S.T., Thompson, D., Nicklas, T. and Baranowski, T., 2019. “Healthy Habits, Healthy Girls—Brazil”: an obesity prevention program with added focus on eating disorders. Eating and Weight Disorders-Studies on Anorexia, Bulimia and Obesity, 24(1), pp.107-119.

Pandita, A., Sharma, D., Pandita, D., Pawar, S., Tariq, M. and Kaul, A., 2016. Childhood obesity: prevention is better than cure. Diabetes, metabolic syndrome and obesity: targets and therapy, 9, p.83.

Salas, X.R., Forhan, M., Caulfield, T., Sharma, A.M. and Raine, K., 2017. A critical analysis of obesity prevention policies and strategies. Canadian Journal of Public Health, 108(5), pp.e598-e608.

Taherdoost, H., 2016. Sampling methods in research methodology; how to choose a sampling technique for research. How to Choose a Sampling Technique for Research (April 10, 2016).

Tourangeau, R., 2018. Choosing a mode of survey data collection. The Palgrave handbook of survey research, pp.43-50.

Ward, D.S., Welker, E., Choate, A., Henderson, K.E., Lott, M., Tovar, A., Wilson, A. and Sallis, J.F., 2017. Strength of obesity prevention interventions in early care and education settings: A systematic review. Preventive Medicine, 95, pp.S37-S52.

Wu, C. and Thompson, M.E., 2020. Basic Concepts in Survey Sampling. In Sampling Theory and Practice (pp. 3-15). Springer, Cham.

Yang, S. and Kim, J.K., 2020. Statistical data integration in survey sampling: A review. Japanese Journal of Statistics and Data Science, 3(2), pp.625-650.

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