Chapter 1

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Chapter 1

  1. 1. Quote of the DayOh, people can come up with statistics to prove anything. 14% of people know that. ---Homer Simpson What are Statistics?
  2. 2. Chapter 1:The Nature ofProbability and Statistics Section 1: Descriptive and Inferential Statistics
  3. 3. Stats in Daily Life Of the people in the US, 14% said they feel happiest in June, and 14% said they feel happiest in December. The average in-state college tuition and fees for 4-year pubic college is $5,836. Every day in the US about 120 golfers claim that they made a hole-in-one. 4 out of 5 doctors leaves one doctor.- Chevy Chase
  4. 4. What is Statistics? The science of conducting studies to collect, organize, summarize, analyze and draw conclusions from data.
  5. 5. What is Data? The values that the variables can assume. A collection of values forms a Data Set  Each Value in the data set is called:  Data Value or  Datum
  6. 6. What is a variable? A characteristic or attribute that can assume different values.
  7. 7. Types of Statistics1. Descriptive Statistics  Consists of the collection, organization, summarization, and presentation of data  Ex: Government Census  Taken every ten years  Describes average income, family size, etc.. What does this mean?  Basically used to describe a situation.
  8. 8. Types of Statistics2. Inferential Statistics  Consists of generalizing from samples to populations, performing estimations and hypothesis tests, determining relationships among variables, and making predictions.  Ex: Winning the lottery  1 in a million What does this mean ?  Used to predict the outcome of an event.
  9. 9. What is the difference between aPopulation and a Sample?  Population- consists of all subjects that are being studied.  Sample- is a group selected from a population.
  10. 10. PopulationSample
  11. 11. Assignment Page 26  #’s 1-6
  12. 12. Section 2: Types of Variables Qualitative Variables:  Variables that can be placed into distinct categories, according to some characteristic or attribute.  Ex: Gender, Eye color, Geographic Location
  13. 13. 2 Types of Variables Quantitative Variables:  Variables that are numerical and can be ordered or ranked.  Ex: Age, height, weight, body temp  Classified by two groups  Discrete Variables  Continuous Variables
  14. 14. Practice Page 26 #8
  15. 15. Discrete Variables Assume values that can be counted Assigned numbers such as 0,1,2,3,… Ex:  # of children  # of students
  16. 16. Continuous Variables Can assume an infinite number of values between any two specific values. Obtained by measuring Often include fractions and decimals. Ex:  Temperature  Time  Length
  17. 17. Practice Page 27 #9
  18. 18. Measurement Scale Used to categorize, count, or measure variables. Types:  Nominal  Ordinal  Interval  Ratio
  19. 19. Nominal Level of Measurement Classifies data into mutually exclusive, exhausting categories in which no order or ranking can be imposed on the data. Ex:  Male/Female  Single/Married/Divorced/Widowed/Separated  Democratic/Republican
  20. 20. Ordinal Level of Measurement Classifies data into categories that can be ranked; however, precise differences between the ranks do not exist. Ex:  Letter Grades (A, B, C, D, F)  1st, 2nd, 3rd, etc  Small, Medium, Large  Freshman, Sophomores, Juniors, Seniors
  21. 21. Interval Level of Measurement Ranks data, and precise differences between units of measures do exist: however, there is no meaningful zero. Ex:  Temperature: 72°F and 73°F, difference of 1°F, but 0°F does not mean no heat present  IQ: 109 and 110, difference of 1 point, but 0 does not mean there is no intelligence.
  22. 22. Ratio Level of Measurement Possesses all the characteristics of interval measurements, and there exists a true zero. In addition, true ratios exists when the same variables is measured on two different members of the population. Ex:  Salary  Time  Age
  23. 23. Practice Page 26 #7
  24. 24. Section 3: Data Collection andSampling Techniques. Types:  Random  Systematic  Stratified  Cluster
  25. 25. Random Sampling Selection based on chance or random numbers. Procedure:  Assign number to each subject in population  Select numbers at random from “hat”
  26. 26. Random Sampling1 2 3 4 5 6 78 9 10 11 12 13 1415 16 17 18 19 20 21
  27. 27. Systematic Sampling Procedure:  Number each subject in population  Select every kth subject Example:  Population: 100 Sample: 10  Kth term: 100/10=10  1, 11, 21, 31, 41, 51, 61, 71, 81, 91
  28. 28. Systematic SamplingPopulation: 21 Sample: 721/7=3: kth term is 3. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21
  29. 29. Stratified Sampling Procedures:  Population divided into groups called: Strata  Groups have common characteristic needed for study.  Samples randomly selected from each strata
  30. 30. Stratified Sampling
  31. 31. Cluster Sampling Population is divided into groups called: Clusters Select some clusters Survey every member of the cluster for sample Used with large populations
  32. 32. Cluster Sampling
  33. 33. Other sampling methods Convenience sampling  Use subjects that are convent  Ex: asking people as they enter the mall Sequential sampling Double sampling Multistage sampling
  34. 34. Convenience Sampling Do you want to take a survey?
  35. 35. Practice Page 27 #12
  36. 36. Section 4: 2 Types of Studies Observational Study  Researchers merely observe what is happening or what has happened in the past  Try to draw conclusions based on these observations.  Ex: studying creatures in the wild  “Meerkat Manor”
  37. 37. Section 4: 2 Types of Studies Experimental study  Researchers manipulate one of the variables  Tries to determine how to the manipulation influences other variables.  Ex: New medication and placebos
  38. 38. Practice Page 27-28 #17
  39. 39. Statistical Studies include…. Independent variables  In an experimental study is the one that is being manipulated by the researcher.  Also called: Explanatory variable Dependent variables  Resultant variable  Also called: Outcome variable
  40. 40. Misuses of Statistics Suspect Samples  Too small  Convenience  Volunteers Changing the subject  Increase of 3%  Increase of $600,000
  41. 41. Misuses of Statistics Detached Statistics- no comparison  “Works 5 times faster”  “1/3 fewer calories” Implied Connection  “Eating fish may help you achieve better in school”
  42. 42. Misuses of Statistics Misleading Graphs- Chapter 2 Faulty Survey Questions  “Do you feel there should be a 4 day school week?”  “Do you feel there should be a 4 day school week from 4 am to midnight?”
  43. 43. Section 1-6: Computers andCalculators Computer and Calculators GOOD
  44. 44. End of Chapter 1

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