Math 114-Quiz 3 - Quiz 3 PDF

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Math 114-Quiz 3

1. True or False: The area under the entire normal curve is 1. True 2. True or False: The normal curve is bell-shaped. True 3. Empirical Rule Graph Individuals People or objects included in the study 4. Variable Is a characteristic of the individual to be measured or observed 5. Quantitative Variable Has a value or numerical measurement for which operations such as addition or averaging makes sense 6. Qualitative Variable Describe an individual by playing the individual into a category or group such as male or female 7. Population Data The data that is from every individual of interest 8. Sample Data The data that is only from some of the individuals of interest (A sample) 9. Population Parameter Numerical measure that describes an aspect of a population ("All") 10. Sample Statistic A numerical measure that describes an aspect of a sample ("Sample" "Some") 11. Nominal Level of Measurement Data that consists of names, labels, or categories

12. Ordinal Level of Measurement Data that can be arranged in order. However, the data values differences either cannot be determined or are meaningless 13. Interval Level of Measurement Data that can be arranged in order. However, the data values differences either cannot be determined or are meaningless 14. Ratio Level of Measurement Data that can be arranged in order. In addition, both differences between data values are meaningful. Data at the ratio level has a true zero 15. Identify the type of data: Name of four Native American pueblos from the population of names of all Native American pueblos in Arizona and New Mexico Nominal 16. Identify the type of data: In a high school graduating class of 319 students, Jen ranked 25th and June ranked 19th and Julia ranked 15th Ordinal 17. Identify the type of data: Body temperatures of trout in the Yellow Stone River Interval 18. Identify the type of data: Length of trout swimming in river Ratio 19. Identify the type of data: The senator's name is Sam Wilson Nominal 20. Identify the type of data: The senator is 58 years old Ratio 21. Identify the type of data: The senator's total taxable income last year was $878,314 Ratio 22. Identify the type of data: The senator's marital status is "married" Nominal 23. Identify type of data: The senator surveyed his constituents regarding his proposed water protection bill. The choices for the response were strong support, support, neutral, against, or strongly against Ordinal

24. Identify the type of data: A leading news magazine claims the senator is ranked seventh for his voting record on bills regarding public education Ordinal 25. Descriptive Statistics Involve methods of organizing, picturing, and summarizing information from samples or populations 26. Inferential Statistics Involves methods of using information from a sample to draw conclusions regarding the population 27. Simple Random Sampling Of n measurements from a population is a subset of the population selected in such a manner that every sample size n from the population has an equal change of being selected 28. Random Sampling Use a simple random sample from the entire population 29. Stratified Sampling Divide the entire population into subgroups called strata. The strata are based on specific characteristics such as age, income, education, eat. Draw random samples from each strata 30. Systematic Sampling Number all members of the population sequentially then, from a starting point selected at random, include every nth member of the population in the sample 31. Cluster Sampling Divide the entire population into preexisting segments of clusters. The clusters are often geographic. Make a random selection of clusters. Include every member of each selected cluster in the sample 32. Multistage Sampling Use a variety of sampling methods to create successively smaller groups at each stage. The final sample consists of clusters 33. Convince Sampling Create a sample by using data from population members that are readily available 34. Sampling Frame List of individuals from which a sample is actually selected

35. Under Coverage Results from omitting population members from the sample frame 36. Frequency Table How to Find the Class Width (Largest Data - Smallest Data) ÷ Number of classes Lower Class Limit Lowest data value that can fit into a class Upper Class Limit Lower limit + Class width Class Frequency Tally marks Class Midpoint How to find lower/upper boundaries • Add .5 to upper limit • Subtract .5 from lower limit 37. Relative Frequency Frequency ÷ Number of Data values 38. Outliers Extreme values that don't appear to belong with the rest of the data 39. Cumulative Frequency For a class is the sum of the frequencies for that class and all previous classes 40. Stem-and-Leaf Plots Method of exploratory data analysis that is used to rank-order and arrange data into groups 41. Mode The most frequent number 42. Median • Middle Number • Subtract the two and divide by 2

Median in Large Data Sets (n+1)÷2 = The position of the median 43. Mean Sum of all entries ÷ Number of entries 44. Range Largest value - Smallest value 45. Coefficient of Variance (S÷Mean) • 100 (Population Standard Deviation ÷ Population Mean) • 100 46. How to Compute Quartiles 1. Order from smallest to largest 2. Find the median (Q2) 3. The first quartile is then the median of the lower half of data 3. The third quartile is the median of the upper half of the data 47. Box-And-Whisker Plot 48. Properties of a Normal Curve • The curve is bell-shaped, with the highest point at µ • The curve is symmetrical about a vehicle line through µ 49. Z-Value Equation Z-Value Gives the number of standard deviations between the original measurement x and the mean µ of the x distribution 50. Raw Score X Equation X = Z-Score + µ 51. Standard Normal Distribution Normal distribution with mean µ=0 and standard deviation = 1 52. What does the standard normal distribution tell us? • The mean is zero • The standard deviation is 1 • Any normal distributions can be converted to a standard normal distribution by converting all the measurements to standard z-scores

53. How to determine whether data has normal distribution for a histogram The histogram should be roughly bell-shaped 54. How to determine whether data have normal distribution for outliers There should not be more than one outlier. one way to check for outliers is to use a box-and-whisker plot. Recall that outliers are those data values that are = above q3 by an amount greater than 1.5 X interquartile range = below q1 by an amount greater than 1.5 x interquartile range 55. Population Standard Deviation Equation σ = (Square Root) σ² 56. Sample Standard Deviation Equation s = (Square Root) s² 57. Sample Mean Equation x = (∑x)÷n 58. Population Mean Equation µ = (∑x)÷N 59. Sample Variance Equation s² = (∑x-x)²÷(n-1) 60. Population Variance Equation σ² = (∑x-µ)² ÷ N 61. Convert x value to z-score x = z σ+ µ 62. What does s² stand for? Sample Variance 63. What does x Stand for? Sample Mean 64. What does S stand for? Sample Standard Deviation 65. What does σ² stand for? Population Variance 66. What does σ stand for? Population Standard Deviation...