1 2 Sampling and Data Collection Plan The scenario is to research whether in Maranon company the \"on my way\" method of shipping when used to leads to low shipment costs. The two variables used will be shipping method selected used by a customer and the other variable is shipment costs. Population is a set of similar items or events which is of interest for some question, experiment or a particular research. In our scenario, population of all customers of Maranon shipment services including the potential customers. Part II: Sampling and Proportions True population proportion represents the fraction of people in a certain population who have a given characteristic. In this case our target population will be the customers who have used the Maranon shipment services and are likely to use the services in the next 20 days. Sampling element will be use of observation whereby I will make use of data mining .I will use this method since I have to get specific data from a large database of a lot of information. Maranon company has the information about their customers it will be possible for me to get the target population then I use simple random sampling to select my sample from the target population .Of which after getting my sample size I will get to know the revenues got by the company from the other given methods of shipment used .Then I will put in place a pilot study on the shipment method known as \"on my way \" method of shipment ,this will be implemented by using the method of \"on my way\" to deliver to customers who are in the sample size only, a study that will take 20 days. Then I will calculate the mean revenue for all elements in the sample size having used \"on my way\" for delivery. Sampling Method 3 The method of sampling is simple random sampling to pick elements from the target population. Recall that for this sample to be unbiased estimator of the population it is compulsory that we use an appropriate formula to calculate the sample size from population size. And in this case we shall use slovin's formula to calculate the sample size since we know a little concerning this population which states that Sample size(n)=N/(1+ne) where N=population size, e=error tolerance/significance level. Validity and reliability will achieved by making sure the system is checked and evaluated for any failures before the pilot study starts and any faults must be detected and rectified before the study starts otherwise we will not have problems of unresponse and missing data since the records are available in complete. No personal data will be disclosed to the researcher since it's not needed for this analysis. Part II: Collecting Data The relevant data will be collected by examining data from Maranon company on shipment to get the data on both means of using the method of \"on my way\" on the pilot study and also mean on other methods used. To achieve this we shall use data mining. The relevant data obtained from the Maranon database will organized then in the computer which I will use for data analysis but before I start working on it I will store a stencil or a master copy in a different place in case of malfunctioning during the data analysis process it can be recovered. Calculations Taking the estimated population to be =200, estimated other methods mean revenue=$100, Estimated \"on my way \"method mean revenue=150, estimate standard deviation 4 of population=9.4 Sample proportion (n)=N/(1+Ne) where N=population size, e=error tolerance/significance level. N=200/(1+200*0.05^2)=133 Margin of error = critical value* estimate standard deviation of population =1.96* 9.4/sqrt(133) =1.6 References 5 Lind, D., Marchal, W., & Wathen, S. (2015). Statistical Techniques in Business Economics (Vol. 16). New York, NY, USA: McGraw Hill Education. Ritala, Paavo. (2014) Coopetitionbased Business Models: The Case of Amazon.com. Industrial Marketing Management 43 (2). P 236249. Retrieved from: http://www.sciencedirect.com.contentproxy.phoenix.edu/science/article/pii/S0019850113002150 Descriptive Statistics and Interpretation Example QNT/561 Version 8 1 University of Phoenix Material Descriptive Statistics and Interpretation Example Interpretation Phrases Central Tendency: Mean = average of a set of data Median = half or equal number of data is above and half or equal number of data is below. It is a midpoint in an ordered (sorted) set of data, a physical location Mode = most frequent value in a set of data Dispersion: Standard deviation = variation Interquartile range (IQR) = the middle 50% of the data Range = the difference between the largest and smallest value of the data Confidence Interval: (data must be normal) There is 95% confidence that the population average is between _____ and ____ units. Normal or significantly skewed data: MegaStat: Descriptive statistics Normal curve goodness of fit p-value Normal, p-value > .05 Significantly Skewed, p-value < .05 Histogram: Eyeball the histogram. Normal data will have a symmetrical or slightly skewed shape. Significantly Skewed shape will have extreme skewness Use phrase combinations: Normally distributed: Mean and Standard Deviation, Not normally distributed: Median and IQR Copyright 2015 by University of Phoenix. All rights reserved. Descriptive Statistics and Interpretation Example QNT/561 Version 8 2 Descriptive Statistics Body Weight (Lbs.) Central Tendency: Dispersion: Count: Min/Max: Confidence Interval: Mean = 149 Lbs. Standard deviation = 30 Lbs. 100 99 pounds and 234 Lbs. 144 to 155 Lbs. See the histogram in Appendix A, and descriptive statistics in Appendix B. Age Distribution is not normally distributed Central Tendency: Dispersion: Count: Min/Max: Confidence Interval: Median = 36 years Interquartile Range = 20.5 years / 2 = 10 years 100 18 years and 74 years Not applicable (data is not normally distributed) See the histogram in Appendix A, and descriptive statistics in Appendix B. A scatter plot is in Appendix C. Education Level Thirteen percent of the subjects have no high school degree while 44% have high school degree. Forty three percent have a college or college graduate degree. See the bar chart in Appendix D. Descriptive Statistics Interpretation Interpretation Body Weight One hundred subjects were randomly selected. Their body weight was observed between 99 and 234 pounds. Their average weight was 149 pounds, with a variation of plus or minus 30 pounds. One half Copyright 2015 by University of Phoenix. All rights reserved. Descriptive Statistics and Interpretation Example QNT/561 Version 8 3 or more were above 149 pounds. There is 95% confidence that the population body weight average is between 144 and 155 pounds. Age The data was significantly skewed. One hundred subjects were randomly selected. Their ages were between 18 and 74 years, with a variation of plus or minus 10 years. One half or more subjects were 36 years of age or older. The middle half of the subjects' ages fell between 27 and 47 years. The most frequent age was 36 years. Copyright 2015 by University of Phoenix. All rights reserved. Descriptive Statistics and Interpretation Example QNT/561 Version 8 APPENDIX A Body Weight and Age Histograms Copyright 2015 by University of Phoenix. All rights reserved. 4 Descriptive Statistics and Interpretation Example QNT/561 Version 8 APPENDIX B Descriptive Statistics Body Weight and Age Copyright 2015 by University of Phoenix. All rights reserved. 5 Descriptive Statistics and Interpretation Example QNT/561 Version 8 APPENDIX C Scatterplot Body Age versus Weight Copyright 2015 by University of Phoenix. All rights reserved. 6 Descriptive Statistics and Interpretation Example QNT/561 Version 8 APPENDIX D Bar Chart Education Level Copyright 2015 by University of Phoenix. All rights reserved. 7 Running head: DESCRIPTIVE STATISTICS 1 Descriptive Statistics Name QNT/561 Date Instructor's Name DESCRIPTIVE STATISTICS 2 Descriptive Statistics Determine the appropriate descriptive statistics. Note: If the data was normally distributed, use the mean and standard deviation. If the data was skewed significantly, use the median and interquartile range. Numeric Variable Name1 Distribution: State if not normally distributed Central Tendency: Dispersion: Number: Min/Max: Confidence Interval: (if distribution is normal) Numeric Variable Name2 (if applicable) Distribution: State if not normally distributed Central Tendency: Dispersion: Number: Min/Max: Confidence Interval: (if distribution is normal) Attribute Variable Name (if applicable) Create a bar chart. Describe the proportions. DESCRIPTIVE STATISTICS Descriptive Statistics Interpretation Numeric Variable Name1 Describe the variable in laymen terms. Numeric Variable Name2 (if applicable) Describe the variable in laymen terms. 3 DESCRIPTIVE STATISTICS 4 Appendix A Raw data used in the analysis Fit data to one page. DESCRIPTIVE STATISTICS 5 Appendix B Charts and Tables This part of the paper will include items that are then cited in the body of the paper. Usually, large items are placed here not to distract from reading the paper. DESCRIPTIVE STATISTICS 6 Appendix C Descriptive Statistics This part of the paper will include descriptive statistics. 1 2 Sampling and Data Collection Plan The scenario is to research whether in Maranon company the \"on my way\" method of shipping when used to leads to low shipment costs. The two variables used will be shipping method selected used by a customer and the other variable is shipment costs. Population is a set of similar items or events which is of interest for some question, experiment or a particular research. In our scenario, population of all customers of Maranon shipment services including the potential customers. Part II: Sampling and Proportions True population proportion represents the fraction of people in a certain population who have a given characteristic. In this case our target population will be the customers who have used the Maranon shipment services and are likely to use the services in the next 20 days. Sampling element will be use of observation whereby I will make use of data mining .I will use this method since I have to get specific data from a large database of a lot of information. Maranon company has the information about their customers it will be possible for me to get the target population then I use simple random sampling to select my sample from the target population .Of which after getting my sample size I will get to know the revenues got by the company from the other given methods of shipment used .Then I will put in place a pilot study on the shipment method known as \"on my way \" method of shipment ,this will be implemented by using the method of \"on my way\" to deliver to customers who are in the sample size only, a study that will take 20 days. Then I will calculate the mean revenue for all elements in the sample size having used \"on my way\" for delivery. Sampling Method 3 The method of sampling is simple random sampling to pick elements from the target population. Recall that for this sample to be unbiased estimator of the population it is compulsory that we use an appropriate formula to calculate the sample size from population size. And in this case we shall use slovin's formula to calculate the sample size since we know a little concerning this population which states that Sample size(n)=N/(1+ne) where N=population size, e=error tolerance/significance level. Validity and reliability will achieved by making sure the system is checked and evaluated for any failures before the pilot study starts and any faults must be detected and rectified before the study starts otherwise we will not have problems of unresponse and missing data since the records are available in complete. No personal data will be disclosed to the researcher since it's not needed for this analysis. Part II: Collecting Data The relevant data will be collected by examining data from Maranon company on shipment to get the data on both means of using the method of \"on my way\" on the pilot study and also mean on other methods used. To achieve this we shall use data mining. The relevant data obtained from the Maranon database will organized then in the computer which I will use for data analysis but before I start working on it I will store a stencil or a master copy in a different place in case of malfunctioning during the data analysis process it can be recovered. Calculations Taking the estimated population to be =200, estimated other methods mean revenue=$100, Estimated \"on my way \"method mean revenue=150, estimate standard deviation 4 of population=9.4 Sample proportion (n)=N/(1+Ne) where N=population size, e=error tolerance/significance level. N=200/(1+200*0.05^2)=133 Margin of error = critical value* estimate standard deviation of population =1.96* 9.4/sqrt(133) =1.6 References 5 Lind, D., Marchal, W., & Wathen, S. (2015). Statistical Techniques in Business Economics (Vol. 16). New York, NY, USA: McGraw Hill Education. Ritala, Paavo. (2014) Coopetitionbased Business Models: The Case of Amazon.com. Industrial Marketing Management 43 (2). P 236249. Retrieved from: http://www.sciencedirect.com.contentproxy.phoenix.edu/science/article/pii/S0019850113002150