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Flashcards

Unit 1

Summer Davis Elementary Statistics College Student Inglês 66 flashcards

Unit 1

Flashcards do conjunto (66)

  1. 1StatisticsThe science of collecting, describing, and analyzing data
  2. 2What are the subjects/objects in a data table called?cases or units
  3. 3What are the characteristics recorded for each case?variables
  4. 4Cases are normally tracked using rows or columns?rows
  5. 5Variables are normally tracked using rows or columns?columns
  6. 6Categorical variabledivides cases into groups, placing each case into exactly one of two or more categories
  7. 7Quantitative variablemeasures or records a numerical quantity for each case
  8. 8Explanatory variablea variable that helps us understand or predict the values of another variable
  9. 9Response variablea variable that is understood or predicted by another variable
  10. 10Populationincludes all individuals or objects of interest
  11. 11Samplea subset of a population
  12. 12Statistical inferencethe process of using data from a sample to gain information about the population
  13. 13Sampling biasoccurs when the method of selecting a sample causes the sample to differ from the population in some relevant way.
  14. 14How to avoid sampling bias?Try to obtain a sample that is representative of the population.
  15. 15Simple random sampleThe population have the same chance of becoming the sample - avoids sampling bias
  16. 16Biasexists when the method of collecting data causes the sample data to inaccurately reflect the population
  17. 17AssociationTwo variables are associated if values of one variable tend to be related to the values of another variable
  18. 18CausationTwo variables are causally associated if changing the value of one variable influences the value of the other variable
  19. 19Confounding variable(aka: confounding factor/lurking variable)
    a third variable that is associated with both explanatory and response. Can offer a plausible explanation for an association between two variables of interest.
  20. 20Observational studya study in which the researcher does not actively control the value of any variable, but simply observes the values as they naturally exist
  21. 21Experimenta study in which the researcher actively controls one or more of the explanatory variables
  22. 22Randomized experimentthe value of the explanatory variable for each case is determined randomly, before the response variable is measured.
  23. 233 Explanations for why an association may be observed in sample data:1. There is a causal association
    2. There is an association, but it is due to confounding
    3. There is no actual association; the association seen in the sample data occurred by random chance
  24. 24Treatmentsvalues of the explanatory variable which the researcher controls
  25. 25Randomized comparative experimentrandomly assign cases to different treatment groups and then compare results on the response variable(s)
  26. 26Matched pairs experimenteach case gets both treatments in random order, examine individual differences in the response variable between the two treatments.
  27. 27Control groupNothing is done to this group that might directly influence the response variable
  28. 28Placebo effectIf people believe they are getting an effective treatment, they may experience the desired effect regardless of whether the treatment is any good
  29. 29Single-blind experimentparticipants are not told which group they are in
  30. 30Double-blind experimentparticipants and not told which group they are in and the people interacting with the participants/recording results do not know who is in each group
  31. 31Frequency tablegives the counts in each category of a categorical variable
  32. 32Proportiona summary statistic out of 1 that helps describe the categorical variable (also called relative frequencies):
    Number in that category
    _________________________________
    Total number
  33. 33What kind of chart is this?Bar chartWhat kind of chart is this?
  34. 34What kind of chart is this?Pie chartWhat kind of chart is this?
  35. 35Notation for Proportionsample: p̂ ("p - hat")
    population: p
  36. 36Two-Way Tableshows the relationship between two categorical variables. Categories for one variable are listed down the side (rows) and categories for the second are listed across the top (columns)
  37. 37What kind of chart is this?A segmented bar chartWhat kind of chart is this?
  38. 38What kind of chart is this?Side-by-side bar chartsWhat kind of chart is this?
  39. 39Comparative plotsGraphs that allow us to compare groups in a categorical variable
    ex: segmented bar chart, side-by-side bar chart
  40. 40What three questions do we consider when describing a single quantitative variable?1. What is the general shape of the data?
    2. Where are the data values centered?
    3. How do the data vary?
  41. 41What is this?A dotplotWhat is this?
  42. 42Outlieran observed value that is notably distinct from the other values in a dataset. Usually much larger or smaller than the rest.
  43. 43What type of graph is this?A histogramWhat type of graph is this?
  44. 44Symmetric distributionwe can fold the plot over a vertical center line and the two sides match closely
  45. 45How would you describe this histogram's distribution?Symmetric & bell-shapedHow would you describe this histogram's distribution?
  46. 46How would you describe these histograms' distribution?Skewed to the rightHow would you describe these histograms' distribution?
  47. 47How would you describe this distribution?Skewed to the leftHow would you describe this distribution?
  48. 48How would you describe this distribution?Symmetric but not bell-shapedHow would you describe this distribution?
  49. 49MeanSum of values divided by number of values
    Σx
    _____
    n
  50. 50Notation for mean sample / populationsample: x̄ ("x-bar")
    population: μ (mu)
  51. 51Median(splits the data in half)
    - the middle entry if an ordered list has odd # of entries
    -the average of the middle two values if an ordered list has an even # of entries
  52. 52Resistancea statistic is resistant if it is relatively unaffected by extreme values - the median is resistant, while the mean is not
  53. 53Is Mean <, >, or = to Median?Mean < MedianIs Mean &lt;, &gt;, or = to Median?
  54. 54Is Mean <, >, or = to Median?Mean = MedianIs Mean &lt;, &gt;, or = to Median?
  55. 55Is Mean <, >, or = to Median?Mean > MedianIs Mean &lt;, &gt;, or = to Median?
  56. 56Standard deviationA statistic that measures how much variability there is in the data - how much spread there is in a sample
  57. 57Standard Deviation notation sample populationsample = s
    population = σ
  58. 58The 95% RuleIf data is approximately symmetric & bell-shaped, about 95% of the data should fall within two standard deviations of the mean.The 95% Rule
  59. 59Z-scorehow many standard deviations the value is from the mean
    x - x̄
    ___________
    s
  60. 60P(th) Percentilethe value of a quantitative variable which is greater than P percent of the data
  61. 61Five Number Summarymin, Q1, median, Q3, max
  62. 62RangeMax - min
  63. 63Interquartile range (IQR)Q3 - Q1
  64. 64Choosing measures of center & spreadMean & Standard Deviation:
    -Use all data values
    -Not resistant to outliers
    Five Number Summary:
    -if there are outliers / heavily skewed data, FNS can provide more info
  65. 65boxplot- A numerical scale appropriate for values
    - A box stretching from Q1 to Q3
    -A line that divides the box at the median
    -A line from each quartile to most extreme non-outlier
    -Each outlier plotted individually
  66. 66IQR method for detecting outliersA) Smaller than Q1 - 1.5(IQR)
    B) Larger than Q3 + 1.5(IQR)

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College Student Elementary Statistics FlashCards sobre Unit 1, criado por Summer Davis em 21-01-2023.
Criado por
Summer Davis
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