MATH 309 - Statistics Portfolio Project - Weekly Case Study 3 This Weekly Case Study is worth 4% of your overall grade Outcomes Completing this Assessment will help you to: Organize data for analysis in the form of graphs, tables, and frequency distributions. Calculate statistical data for measures of central tendency and dispersion. Investigate dispersion through normal distributions using range, mean, standard deviation, and zscores. Measure location, variation, probabilities, distributions, and expectations. [Adapted from \"Real Statistics - Real Decisions\MATH-309 PORTFOLIO PROJECT: WEEK 1 CASE STUDY Portfolio Project: Week 1 Case Study Angela R. Harris Math/309 S. Talton November 05, 2016 Statistical Concepts 1 MATH-309 PORTFOLIO PROJECT: WEEK 1 CASE STUDY Statistics is one of the diversified field that gives facts and assumptions about statistical data that helps in problem solving and decision making. In this week's session, various statistical concepts were taught. It was worth noting that the session introduced how to organize data for statistical analysis. Data analysis concepts here involved the use of frequency distributions, graphs and tables. The measures of dispersion and tendency were taught and clear and concise explanation of how to interpret and investigated the data to determine the properties of the data. Therefore, these statistical concepts will be employed in this assignment as they assist in data interpretation and presentation. Other questions that can be incorporated in the research are; 1) What is the main reason you travel by air? Please tick one box. a) Business b) Holidays c) Visiting friends/family 2) Which places do you usually like visiting? a) Africa b) Asia c) America d) Australia e) Others 2. How to do it a b c d What sampling technique would you use to select the sample for the study? Why? The sampling technique that is most appropriate for this study is a simple random sampling. This is because everyone will have a change to be selected. Will the technique you chose give you a sample that is representative of the population? Yes. The technique will give the required sample as it's a fair way of selecting a sample Describe exactly how you would complete the sampling method to collect the data. To get started, a sampling frame is organized and select the sample required that you wish to have in your final sample. Identify possible flaws or biases in your study The possible bias is the luck of draw and there is no good representation of the subgroups in the population. 3. Data classification 2 MATH-309 PORTFOLIO PROJECT: WEEK 1 CASE STUDY a What type of variables do you expect to collect: qualitative, quantitative or both? Why? Give an example for each type of data using the above sample questions or other questions that you would think appropriate for this survey. The type of variables to collect will be qualitative as we are focusing on getting the information. These variables can be about some routine, behavior of the customers and desires. b For each variable, indicate the level of measurement. The variables will fall under nominal and ordinal scale c Identify the population and sample that will be represented in your study. The population will entail the air travel industry publication readers while the sample will be the portion of readers selected to participate. d For one of the above variables, identify a parameter and a matching statistic (you can make up the data) that might result from your study 4. Metacognition The variable will be the routine, which will have the sample mean as the statistic Statistical data collection requires a keen observation and understanding of the sample population where the researcher would wish to collect data from. The concepts learned aided in the collection and analysis of the data that has led to the conclusion of the populations' behavior. The measures of dispersion and central tendency gave impeccable information that can be utilized for future reference. References: Adapted from \"Real Statistics -Real Decisions\Running header: PROBABILITY AND DISTRIBUTION Probability and Distribution Student's name University name 1 PROBABILITY AND DISTRIBUTION 2 Probability and distribution 1. Welcome paragraph Probability and distributions were the main statistical concepts that were deeply analyzed. These statistical concepts were employed in studying the parameters of different datasets. The concepts of distribution involved studying the histogram and explaining its visual information displayed. Therefore, these concepts would be integrated in this task were we would calculate the probabilities and help in understanding the distribution of the data. 2. What is the probability that it involved a fatal accident? The probability of accidents is calculated as; P (accidents) =91/11000000=0.0000083 3. Look up the definition of a Binomial distribution A binomial distribution has been defined as the probability distribution of a binomial random variable (Von & Drager, 2001). Additional, the number of successes found within a repeated trials within the binomial experiment gives the binomial random variable. The binomial variable usually fall within a specified range. 4. Construct a binomial distribution for n = 11,000,000 and p = 0.0000004 (from above) as well as p = 0.0000008 with x = 0 to 12. x 0 1 2 3 4 p=0.0000004 0.012277329 0.05402027 0.11884463 0.174305495 0.191736069 p=0.0000008 0.000150733 0.001326447 0.005836373 0.017120038 0.037664103 PROBABILITY AND DISTRIBUTION 5 6 7 8 9 10 11 12 3 0.168727747 0.123733674 0.077775441 0.042776483 0.02091294 0.00920169 0.003680674 0.00134958 0.06628885 0.097223681 0.122224087 0.134446518 0.131458827 0.115683766 0.092547002 0.067867788 5. Metacognition The learning skills and knowledge obtained during this week are much essential in statistical analysis. The skills will help me in being able to calculate easily any calculations involving binomial distributions. There are essential concepts of like calculating the probability that will make future data analysis easier. PROBABILITY AND DISTRIBUTION 4 Reference Von, C. E., & Drager, K. (2001). Binomial distribution handbook for scientists and engineers. 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