Descriptive Analysis Exam 1

Question 1

Frequency tables

Answer 1

• Used to present counts and frequencies of discrete or continuous data at any level of measurement
• Must include a clear title, descriptive column names, adequate space and row/column delineation

Question 2

Box and whisker plots

Answer 2

• Used to visualize the range of spread of data

* Only one axis is mathematically meaningful

Question 3

Bar charts

Answer 3

• Used to graph discrete (interval, ratio) / categorical (nominal, ordinal) data
• Ideal for visualizing frequencies and distributions but not ideal for representing trends over time
• Must include title and labeled axes with well-defined units of measurement

Question 4

Histograms

Answer 4

• Similar to bar charts but used to graph numeric data that have been apportioned into discrete categories
• May be used to illustrate changes in a variable over time
• Must include a title and labeled axis with well-defined units of measurement

Question 5

Frequency polygons

Answer 5

• A special kind of line graph in which we place a dot above the midpoint of each class interval and connect the dots
• Being and end with lines touching x-axis
• Can use two sets of data and represent each data with a separate color

Question 6

Pie charts

Answer 6

• Used to represent proportions or relative quantities of values
• Limit amount of represented categories

Question 7

Proportion

Answer 7

• The number of observations with a given characteristic divided by the total number of observations in a given group
• “Parts” divided by the “whole” using the same unit of measurement

Question 8

Rate

Answer 8

• Computed over a specific time-period (per unit of time, for example, per year)
• Typically use a multiplier (for example 1,000, 10,000 or 100,000), which is called the base

Question 9

Prevalence

Answer 9

• Measures the probability of having a disease at a point in time
• Reflects existing disease within a population

Question 10

Incidence

Answer 10

• Measures the number of new cases of a disease (or symptom or problem) that develop in a population at risk within a given period of time
• A.K.A. Cumulative Incidence

Question 11

Sensitivity

Answer 11

• Testing for true positives
• Ability of a diagnostic test to correctly identify individuals with disease
• Proportion of individuals with the disease who are correctly identified by the test
• Have low false negative rates
• True positive + false negative = 1

Question 12

Specificity

Answer 12

• Testing for true negatives
• Ability of a diagnostic test to correctly identify individuals without disease
• Proportion of individuals without the disease who are correctly identified by the test as disease-free
• Have low false positive rates
• True negative + false positive = 1

Question 13

Positive predictive value

Answer 13

• Provides information about how likely it is that the individual does, or does not, have the disease given his/her test result
• Probability that a patient has the disease given that a positive test result was obtained

Question 14

Negative predictive value

Answer 14

• Provides information about how likely it is that the individual does, or does not, have the disease given his/her test result
• Probability that a patient does not have the disease given that a negative test result was obtained

Question 15

4. Describe and interpret receiver operating characteristic (ROC) curves

Answer 15

• ROC curves are used to illustrate the trade-offs between sensitivity (i.e., true positive rate) and the false positive rate
• Each point on the ROC curve represents the sensitivity and false positive rate at a different decision threshold
• Any ROC curve that lies above the chance diagonal has some diagnostic ability
• The area under the chance diagonal is 0.5; the area under the ROC curve for a perfect diagnostic test is equal to 1
• Goal = larger AUC = value of area under closest to 1