Management Sc Session 5 & 6

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Flashcards on Management Sc Session 5 & 6, created by Georgia Tan on 15/10/2015.
Georgia Tan
Flashcards by Georgia Tan, updated more than 1 year ago
Georgia Tan
Created by Georgia Tan over 8 years ago
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What is confirmation bias? Confirmation bias: If the data is there, people often use it in a biased way to support whatever preconceived opinion they have
"accept that the treatment worked if the number of 6’s is larger than a cut-off value c" Do we do this before, during or after we have analyzed the data? before. to avoid confirmation bias
All statistical tests have two elements - name them 1. A measure T, calculated from the data, that allows us to assess the strength of the evidence for the claim 2. An acceptance criterion specified by cut-off value(s) c . One-sided tests (covered in this class) Accept the claim if T > c : the larger T the more evidence for the claim Accept the claim if T < c: the smaller T the more evidence for the claim
What is a false positive error? Testsaysthatthe managerial intervention worked but it actually didn’t
What is a false negative error? Testsaystheintervention didn’t work but it actually did
We should focus on avoiding what kind of error? false positive
significance level = a test procedure’s probability of producing a______ error false positive; , i.e., of producing a positive test result when there is no effect
The significance level is chosen ______ we see the data – The p-value is calculated ____ we see the data – it is a summary statistic of the data before; after
A statistical test only controls the probability of a false ______ error The probability of a false ______ error can be very large positive; negative
The chance of a false negative can be as large as_________ of the test 1- significance level
For single variables, the most important graphs are: (name 3) Histogram Percentile Curve Line Graph
For multiple variables, the most important graphs are: scatter plots
Since intercept and slope are statistics, they have ____ sampling distributions
A high correlation coefficient is always: an indication of a strong relationship
A low correlation coefficient is not an indication that there is no relationship
The significance level tests the claim: “The slope is not zero”...... against the null hypothesis “The slope is zero”
The larger the unknown slope is, the more likely it is that the data will provide evidence that there is a slope
A very small slope can be highly significant in one of the following two situations: A very small slope can be highly significant in one of the following two situations: (a) you have lots of data (the standard error for the slope goes to zero as N goes to infinity) (b) the population regression line fits the data exceptionally well (high R^2)
The confidence interval for the slope gives you information about: the size of the unknown slope of the population regression line
If two variables X and Y are correlated, information about X can improve the prediction of the average of Y
If an omitted variable is the reason for the correlation, then changing X: may not change the omitted variable and hence have no effect on Y
R-square is often used as a “measure of fit” What does this actually mean? R-square can be interpreted as the percentage of variation in the response variable Y that is explained by the variation in the predictors X
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