Flashcards in Midterm Deck (37)
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1
Experiments vs observational studies
Exp. -> can put a control (témoin), researcher has control. Observational study -> we observe. We only associate and do not establish causality
2
Counfounding variable
Variable that can affect both the treatment and the response
3
Random sample
Representative of the population. Not biased
4
3 types of bias
Selection bias. Non-response bias. Measurement errors
5
Selection bias explanation
Subset of the experimental units of population is excluded/no chance of being selected for exp. = not a random sample
6
Non-response bias explanation
Unability to obtain data on all experimental units selected for the sample
7
Measurement error explanation
Inaccuracies in values recorded.
8
Commonly used displays for qualitative data
Pie charts, bar plots
9
Simpson's paradox explanation
Third confounding variable changes the relationship between two other QUALITATIVE variables. Imbalance of the distribution of the categories of the third category with respect to the first two.
10
Graphical displays for quantitative data
Boxplot, dotplot, histogram
11
Adv/Disadv of the dotplot
A : Get to see all the data points + Easy to interpret D: Gets messy quickly if lots of data
12
Adv/Disadv of histograms
A: Easy to pick up on all aspects of quantitative data (centre,spread, etc.) + made by most statistical packages D: Different bin widths can give diff. intepretations
13
Mode
Number (or centre of the bin) that occurs most often (that has the most observations)
14
Frequency vs Percentage
Frequency = number of observ in this bin. Percentage = percentage of total obs. it represents
15
Different possibilities for the mode
Unimodal, Multimodal or no mode
16
Adv/Disadv. of mean
A: Good for estimating pop. mean. + good inferential properties D: Outliers and skewed data
17
Adv/disadv. of median
A: Easy to interpret + not infl. by outliers D: Bad inferential properties + longer to calculate
18
Adv/disadv of mode
A: Highest concentration of data + bimodal data D : Bin width (class definition) matters
19
sample vs pop mean symbols
X bar and μ
20
Sample var/std vs Pop. var/std
S square or S vs sigma square or sigma
21
Different measures of centre
Mean, median, mode
22
Different measures of spread
Range, IQR, Var or std
23
Something particular in variance
squared units
24
% of observations with Z-score values 1,2.3 w/ empirical rule
68, 95, 99.7
25
What are the three quartiles on boxplot
Q1 is 25th percentile, Q2 is median, Q3 is 75th percentile
26
Where whiskers end on boxplot
At most extreme data point within 1.5 IQRs of the EDGE of the box in either direction
27
Extreme outliers in boxplots
Anything beyond 3 IQRs of the EDGE of the box
28
Ad/disadv. or variance
A : Good inferential properties D : Influenced by outliers and skewed data
29
Ad/disadv. IQR
A : Not infl. by outliers D: Bad inferential properties and longer to calculate
30
