The assignment this week is to collect quantitative data for a minimum of 10 days from ONE of your daily activities. Some examples of data collection include: The number of minutes you spend studying every day. The time it takes to cook meals each day. The amount of daily time spent talking on the phone. The amount of time you drive each day. In a paper (1- to 3-page typed Word document), describe the data you are going to collect and how you are going to keep track of the time. Within the paper, incorporate the concepts we are learning in the module, including (but not limited to) probability theory, independent and dependent variables, and theoretical and experimental probability. Discuss your predictions of what you anticipate the data to look like and events that can skew the data. Collect data for at least 10 days. Include at least 3-5 days of data with your SLP 1 submission. Continue collecting data for the remaining days for use in SLP 2. Do you think the data will provide a valid representation of these activities? Explain why or why not. SLP Assignment Expectations Answer all questions posted in the instructions. Use information from the modular background readings and videos as well as any good-quality resource you can find. Cite all sources in APA style and include a reference list at the end of your paper. Note about page length: Your ability to clearly articulate and explain these concepts is being assessed. The page length is a general guideline. A 3- or 4-page paper does not necessarily guarantee a grade of \"A.\" An \"A\" paper would include detailed information and explanations of all the assignment requirements listed above. The letter grade will be based upon demonstrated mastery of the content and ability to articulate and apply the concepts in the assignment. Keep this in mind while writing your paper. Running heading: QUANTITATIVE DATA COLLECTION Quantitative Data Collection Institution: Name: Date: 1 QUANTITATIVE DATA COLLECTION 2 Quantitative Data Collection Quantitative data is numeric data collected in the field for analysis to come up with information (Cuesta, 2013). There are different methods through which data is collected. In the study concerning the module, primary data is collected on the cooking hours in a day. The data will be recorded weekly in a spreadsheet that will be used for analysis. I cook for a family of five. I use different cooking routines for the weekdays as well as the weekends. During the weekdays, I cook two meals which are the breakfast and the dinner. During the weekends, I cook the breakfast, lunch, and dinner. It takes 15 minutes to cook the breakfast and one hour cooking the dinner during the week days. During the weekends, it takes one hour cooking each of the meals. The dependent and the independent variable are used in determining if there exist relationships among data (Bernstein & Bernstein, 2011). In this case, there is regression analysis is used in finding out the relationship between variables. Both dependent and independent variables are critical elements in selecting the data. In the relationship analysis, a confusion of the two results to poor results. The dependent variable in the case study is the time taken to cook the meals. On the other hand, the number of meals is the independent variable. The statement can be expressed as the time it takes to cook meals each day depends on the number of the meals it takes. Skew is any alteration in the data collected from the field. There are different factors that can result to the skewness of the data. Visitors in the family will result to changes in time spent in cooking the meals. It is expected from the data that an increase in the family member will result in a decrease in the cooking time as the amount of food cooked will be little. Therefore, the number of the family members forms another independent variable that can be investigated in the study. Also, a reduction in the family member might result in a reduction in the cooking time. QUANTITATIVE DATA COLLECTION 3 The data collection period will be done for four weeks. During the weeks, the data will be recorded and makes a total of 28days of data collection. Observation is the method of data collection that will be employed. In this case, a timer will be set at the beginning of every cooking activity and stopped when the cooking gas goes off to mean that cooking is over. The final results will be recorded each and every day. Dates will be written alongside the cooking hours. The number of the visitors or a family member leaving the house will be recorded in the spreadsheet. After the 28 days of data collection, the analysis will be done. The data will be valid as the sample size is large and precise conclusions are achieved on larger sample sizes. QUANTITATIVE DATA COLLECTION 4 References Bernstein, S., & Bernstein, R. (2011). Elements of statistics II : inferential statistics. New York: McGraw Hill Professional. Cuesta, H. (2013). Practical data analysis. Birmingham: Packt Publishing. Running heading: QUANTITATIVE DATA COLLECTION Quantitative Data Collection Institution: Name: Date: 1 QUANTITATIVE DATA COLLECTION 2 Quantitative Data Collection Quantitative data is numeric data collected in the field for analysis to come up with information (Cuesta, 2013). There are different methods through which data is collected. In the study concerning the module, primary data is collected on the cooking hours in a day. The data will be recorded weekly in a spreadsheet that will be used for analysis. I cook for a family of five. I use different cooking routines for the weekdays as well as the weekends. During the weekdays, I cook two meals which are the breakfast and the dinner. During the weekends, I cook the breakfast, lunch, and dinner. It takes 15 minutes to cook the breakfast and one hour cooking the dinner during the week days. During the weekends, it takes one hour cooking each of the meals. The dependent and the independent variable are used in determining if there exist relationships among data (Bernstein & Bernstein, 2011). In this case, there is regression analysis is used in finding out the relationship between variables. Both dependent and independent variables are critical elements in selecting the data. In the relationship analysis, a confusion of the two results to poor results. The dependent variable in the case study is the time taken to cook the meals. On the other hand, the number of meals is the independent variable. The statement can be expressed as the time it takes to cook meals each day depends on the number of the meals it takes. Skew is any alteration in the data collected from the field. There are different factors that can result to the skewness of the data. Visitors in the family will result to changes in time spent in cooking the meals. It is expected from the data that an increase in the family member will result in a decrease in the cooking time as the amount of food cooked will be little. Therefore, the number of the family members forms another independent variable that can be investigated in the study. Also, a reduction in the family member might result in a reduction in the cooking time. QUANTITATIVE DATA COLLECTION 3 The data collection period will be done for four weeks. During the weeks, the data will be recorded and makes a total of 28days of data collection. Observation is the method of data collection that will be employed. In this case, a timer will be set at the beginning of every cooking activity and stopped when the cooking gas goes off to mean that cooking is over. The final results will be recorded each and every day. Dates will be written alongside the cooking hours. The number of the visitors or a family member leaving the house will be recorded in the spreadsheet. After the 28 days of data collection, the analysis will be done. The data will be valid as the sample size is large and precise conclusions are achieved on larger sample sizes. QUANTITATIVE DATA COLLECTION 4 References Bernstein, S., & Bernstein, R. (2011). Elements of statistics II : inferential statistics. New York: McGraw Hill Professional. Cuesta, H. (2013). Practical data analysis. Birmingham: Packt Publishing