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Section 1.1 Statistics

Section 1.1 Statistics. Statistics :. Is the science of conducting studies to collect, organize, summarize, analyze and draw conclusions from data. Descriptive Statistics :. Descriptive & Inferential Statistics.

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Section 1.1 Statistics

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  1. Section 1.1Statistics Statistics : Is the science of conducting studies to collect, organize, summarize, analyze and draw conclusions from data.

  2. Descriptive Statistics : Descriptive & Inferential Statistics consists of the collection, organization, summarization and presentation of data. Inferential Statistics : consists of generalizing from samples to population, performing estimation and hypothesis tests, determining relationships among variable, and making predictions.

  3. Population : Population Sample : consists of all subjects (human or otherwise) that are being studied. is a group of subjects selected from population. Sample

  4. A study conducted at a Community College revealed that students who attended class 95 to 100% of the time usually received an A in the class. Students who attended class 80 – 90% of the time usually received a B or C in the class. Students who attended less than 80% of the time usually received a D or an F or eventually withdrew from the class. Based on this information, attendance and grades are related. The more you attend class, the more likely you will receive a higher grade. Read the following and answer the questions :

  5. 1. What are the variables under study? Attendance and Grades 2. What are the data in the study? The data is consist of specific grades and attendance number. The variable are grades and attendance. 3. Are descriptive, inferential, or both types of statistics used? These are descriptive statistic.

  6. 4. What is the population under study? 5. Was a sample collected? If so, from where? While not specified, we probably have data from a sample of a community college students. The population under study is students at a community college . 6. From the information given, comment on the relationship between the variables. Based on the data, it appears that in general, the better you attendance the higher your grade.

  7. Section 1.2Variable and Types of Data Variable : Is a characteristic or attribute that can assume different values.

  8. The classification of variables can be summarized as follow: Qualitative Quantitative Data Discrete Continuous

  9. Classification of Variables Qualitative Variable: are variables that can be placed into distinct categories, according to some characteristics or attributes. Example : If subjects are classified according to gender(male or female), then the variable here is gender which is qualitative. Other examples is geographic locations, eye color, hair color. Quantitative Variable: are numerical and can be ordered or ranked. Example : The variable age is numerical, and people can be ranked according to value of their ages. Other variables like height, weight are also Quantitative variable.

  10. Discrete Variable: Variable and Types of Data Continuous Variable: Assume values that can be counted. Can assume an infinite number of values between any two specific values. They are obtained by measuring. They often include fractions and decimals.

  11. 1) Nominal level of measurement : Measurement level for each variable classifies data into mutually exclusive (non-overlapping), exhausting categories in which no order or ranking can be imposed on the data. - Examples: Zip code, Gender, Eye color, Political affiliation, Religious affiliation, Major field, Nationality.

  12. 2) Ordinal level of measurement : - Examples: classifies data into categories that can be ranked; however, precise differences between the ranks do not exist. Grade (A,B,C,D,F), Judging (first place, second place), Rating scale (poor, good, excellent), Ranking of tennis player.

  13. 3) Interval level of measurement : - Examples: Ranks data, and precise differences between units of measure do exist; however, there is no meaningful zero. SAT score, IQ, Temperature.

  14. 4) Ratio level of measurement : Possesses all the characteristics of interval measurement, and there exists a true zero. In addition, true ratios exist when the same variable is measured on two different members of the population. - Examples: Height, Weight, Time, Salary, Age.

  15. Transportation safety The chart shows the number of job-related injuries for each of the transportation industries for 1998 : Read the following information about the transportation industry and answer the questions : • Industry Number of injuries • Railroad 4520 • Intercity bus 5100 • Subway 6850 • Trucking 7144 • Airline 9950

  16. 1. What are the variables under study? Safe Travel 2. Categorize each variable as quantitative or qualitative. The type of industry is a qualitative variable, while the number of job-related injuries is quantitative. The variable are industry and job-related injuries. 3. Categorize each quantitative variable as discrete or continuous? The number of job-related injuries is discrete.

  17. 4. Identify the level of measurement for each variable. 5. The railroad is shown as the safest transportation industry. Does that mean railroads have fewer accidents than the other industries? Explain. The railroads do show fewer job-related injuries; however, there may be other things to consider. For example, railroads employ fewer people than the other transportation industries in the study. Type of industry is nominal, and the number job-related injuries is ratio.

  18. 6. What factors other than safety influence a person’s choice of transportation? A person’s choice of transportation might also be affected by convenience issue, cost, service, etc. 7. From the information given, comment on the relationship between variables. Answers will vary. One possible answer is that the railroads have the fewest job-related injuries, while the airline industry has the most job-related injuries (more than twice those of railroad industry). The numbers of job-related injuries in the subway and trucking are fairly comparable.

  19. 6. Why was the method more appropriate for this type of data collection? 7. If a convenience sample were obtained, consisting of only adolescence, how would the results of the study be affected? This method allowed me to make sure that I had representation from each area of the united state. Convenience samples may not be representative of the population, and convenience sample of adolescents would probably differ greatly from the general population with regard to the influence of American culture on illegal drug use.

  20. Exercises Page 26 Q 7, 8, 9 , 10

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