Flashcards
Unit 1
Cards in this deck (66)
- 1StatisticsThe science of collecting, describing, and analyzing data
- 2What are the subjects/objects in a data table called?cases or units
- 3What are the characteristics recorded for each case?variables
- 4Cases are normally tracked using rows or columns?rows
- 5Variables are normally tracked using rows or columns?columns
- 6Categorical variabledivides cases into groups, placing each case into exactly one of two or more categories
- 7Quantitative variablemeasures or records a numerical quantity for each case
- 8Explanatory variablea variable that helps us understand or predict the values of another variable
- 9Response variablea variable that is understood or predicted by another variable
- 10Populationincludes all individuals or objects of interest
- 11Samplea subset of a population
- 12Statistical inferencethe process of using data from a sample to gain information about the population
- 13Sampling biasoccurs when the method of selecting a sample causes the sample to differ from the population in some relevant way.
- 14How to avoid sampling bias?Try to obtain a sample that is representative of the population.
- 15Simple random sampleThe population have the same chance of becoming the sample - avoids sampling bias
- 16Biasexists when the method of collecting data causes the sample data to inaccurately reflect the population
- 17AssociationTwo variables are associated if values of one variable tend to be related to the values of another variable
- 18CausationTwo variables are causally associated if changing the value of one variable influences the value of the other variable
- 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. - 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
- 21Experimenta study in which the researcher actively controls one or more of the explanatory variables
- 22Randomized experimentthe value of the explanatory variable for each case is determined randomly, before the response variable is measured.
- 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 - 24Treatmentsvalues of the explanatory variable which the researcher controls
- 25Randomized comparative experimentrandomly assign cases to different treatment groups and then compare results on the response variable(s)
- 26Matched pairs experimenteach case gets both treatments in random order, examine individual differences in the response variable between the two treatments.
- 27Control groupNothing is done to this group that might directly influence the response variable
- 28Placebo effectIf people believe they are getting an effective treatment, they may experience the desired effect regardless of whether the treatment is any good
- 29Single-blind experimentparticipants are not told which group they are in
- 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
- 31Frequency tablegives the counts in each category of a categorical variable
- 32Proportiona summary statistic out of 1 that helps describe the categorical variable (also called relative frequencies):
Number in that category
_________________________________
Total number - 33What kind of chart is this?Bar chart
- 34What kind of chart is this?Pie chart
- 35Notation for Proportionsample: p̂ ("p - hat")
population: p - 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)
- 37What kind of chart is this?A segmented bar chart
- 38What kind of chart is this?Side-by-side bar charts
- 39Comparative plotsGraphs that allow us to compare groups in a categorical variable
ex: segmented bar chart, side-by-side bar chart - 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? - 41What is this?A dotplot
- 42Outlieran observed value that is notably distinct from the other values in a dataset. Usually much larger or smaller than the rest.
- 43What type of graph is this?A histogram
- 44Symmetric distributionwe can fold the plot over a vertical center line and the two sides match closely
- 45How would you describe this histogram's distribution?Symmetric & bell-shaped
- 46How would you describe these histograms' distribution?Skewed to the right
- 47How would you describe this distribution?Skewed to the left
- 48How would you describe this distribution?Symmetric but not bell-shaped
- 49MeanSum of values divided by number of values
Σx
_____
n - 50Notation for mean sample / populationsample: x̄ ("x-bar")
population: μ (mu) - 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 - 52Resistancea statistic is resistant if it is relatively unaffected by extreme values - the median is resistant, while the mean is not
- 53Is Mean <, >, or = to Median?Mean < Median
- 54Is Mean <, >, or = to Median?Mean = Median
- 55Is Mean <, >, or = to Median?Mean > Median
- 56Standard deviationA statistic that measures how much variability there is in the data - how much spread there is in a sample
- 57Standard Deviation notation sample populationsample = s
population = σ - 58The 95% RuleIf data is approximately symmetric & bell-shaped, about 95% of the data should fall within two standard deviations of the mean.
- 59Z-scorehow many standard deviations the value is from the mean
x - x̄
___________
s - 60P(th) Percentilethe value of a quantitative variable which is greater than P percent of the data
- 61Five Number Summarymin, Q1, median, Q3, max
- 62RangeMax - min
- 63Interquartile range (IQR)Q3 - Q1
- 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 - 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 - 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 on Unit 1, created by Summer Davis on 21/01/2023.
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- Summer Davis
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