Shape, Center, and Spread
These are 5 things you need to list when describing a distribution.
What are shape, center, spread, unusual points, and in context?
These are the most common measures of center of a sample of quantitative data.
What are the mean and median?
When comparing two variable quantitative data, using this type of plot allows you to view any potential relations between the variables.
What is a scatter plot?
These two letters are used for the probability of a Type I Error and Type II Error, respectively.
What are ɑ and β?
This is the description of the graph of a normal distribution.
What is a unimodal, bell-shaped, symmetrical graph?
These are the most common measures of variation of a sample of quantitative data.
What are the variance, standard deviation, range, and IQR?
When you linearize an exponential model, apply the logarithm to this variable before performing a linear regression.
What is the response variable?
This term represents the probability of an inference test rejecting the null hypothesis, given that the null hypothesis is false.
What is power?
This type of plot best depicts the shape of a sample of 1-variable quantitative data.
What is a dot plot?
A sample is skewed to the right. Of the mean and median of the sample, this statistic is greater.
Which is the mean?
This statistic represents the percentage of variability that can be explained by the Least Squares Regression Line.
What is the Coefficient of Determination?
Assuming the inherent variability and difference between the hypothesized and true value of the parameter are fixed, increasing these two values increases the power.
What is the sample size and ɑ?
When this type of distribution is depicted on a box plot, the length of each whisker is about half the length of the box.
What is a uniform distribution?
When a sample is skewed, this rule is used to determine any potential outliers.
What is the 1.5*IQR rule, where data greater than Q3 + 1.5*IQR or data less than Q1 – 1.5*IQR are outliers?
A scatter plot has a number of points randomly scattered over a bound, as well as two outliers: point A, which has an x value close to the mean and y value far from the mean, and point B, which has an x value far from the mean and y value close to the mean. This point, of those two points, has greater leverage over the Least Squares Regression Line.
What is point B?
The probability of this type of error can’t be determined without knowing the true value of a parameter.
What is a type II error?
A box plot is drawn with a min of 15, Q1 of 46, median of 53, Q3 of 60, and max of 74. This is the description of that box plot, ignoring outliers.
What is a left skewed distribution, with a median of 53 and IQR of 14, and a minimum of 15 and maximum of 74?
WORK: As the minimum is farther from the median than the maximum, the distribution is left-skewed. As the distribution is skewed, use the median and IQR or range instead of the mean and standard deviation. IQR = Q3-Q1 = 60 – 46 = 14; median is given.
A box plot is drawn with a min of 15, Q1 of 46, median of 53, Q3 of 60, and max of 74. These data are outliers.
What is 15 and 74? WORK: following the 1.5*IQR Rule, data less than 46 – 1.5*(60-46) = 35.5 are outliers, and data greater than 60 + 1.5*(60-46) = 70.5 are outliers. Therefore, 15 and 74 are outliers, and there could be other outliers.
A scientist wants to determine if there is a relationship between height and foot length of men. They obtain a random sample of 25 men and record their heights and foot length in centimeters. After performing a linear regression, the scientist realizes that the tape measure was actually set up 5cm too high, having this effect on the correlation coefficient between height and foot length. Assume assumptions and conditions have been met.
What is no effect?
WORK: An equal linear transformation in all data doesn’t change the fact that the data follow a linear model. Therefore, the correlation coefficient won’t change.
A scientist wants to know whether Archbieduhwae, a recently developed cold medicine, is more effective at treating colds than the leading brand. They perform a two-sampled t-test for difference of mean recovery times in patients with a cold who take Archbieduhwae and patients who take the leading brand. After collecting data, the scientist performs the inference test and gets an insignificant result. After a few months, a doctor notices that patients who were prescribed Archbieduhwae had much quicker recovery times for their colds than with the leading brand, potentially indicating that this type of error occurred.
What is a type II error?