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HES Stat E-100 > Definitions > Flashcards

Definitions Flashcards

1
Q

What is a Categorical Variable?

A

Contains values reflecting different categories. The categorical variable TreatmentType has the nominal values Placebo, Existing_Treatment, and Experimental. In study design contexts, categorical variables could also be referred to as factors, with values as levels

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2
Q

What are Frequency Tables?

A
  • A frequency table lists the categories in a categorical variable and gives the count of observations for each category
  • “Frequency” is just another word for count
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3
Q

What are examples of Categorical Data Visualization?

A
  • Bar Graph
  • Pie Chart
  • Mosiac Plots
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4
Q

What is a Bar Chart or Bar Graph?

A

A bar chart or bar graph is a chart or graph that presents categorical data with rectangular bars with heights or lengths proportional to the values that they represent.

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5
Q

What is a pie chart?

A

A circular statistical graphic, which is divided into slices to illustrate numerical proportion

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6
Q

How do you create a bar graph in R Studio?

A

horiz=TRUE,

bargraph( ~ file-name-here,
data = survey_xlsx_cleaned,
main=”TITLE OF GRAPH” col=c(“color-here”),
xlab=”Name of X-Axis”,
ylab=”Name of Y Axis”)

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7
Q

How do you create a tally in R studio?

A

tally(~ file-name-here, format = “put in counts, proportions, and percentages”, data = survey_xlsx_cleaned, margins=TRUE)

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8
Q

How do you create a pie chart in R Studio?

A

percents <- tally(-FILE-NAME-HERE, format = “percent”, data = survey_xlsx_cleaned)

piepercent<- round(percents, 1)

pie(percents,
radius=1, #radius of pie chart
labels = piepercent,
main = “TITLE OF PIE CHART”,
col = (“turquoise”, “yellow”), # Colors of the pie chart
cex = 0.75) # Label text size
legend(“topright”, #position of Legend
c(“‘No”, “Yes”), #Data Labels
cex = 0.7, #size of the legend
fill = (“turquoise”, “yellow”))* #Color of legend*

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9
Q

What are some things you want to avoid in things to avoid with Data Visualization?

A
  • Biased labeling - Are labels empirically valid?
  • Misleading scales
  • No scale or labels
  • Excessive Visualizations
  • Unequal Areas (Violation of Area Principle)
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10
Q

What is a Contingency Table?

A
  • A contingency table (or cross-tabulation) is a table of counts, proportions, or percentages from two categorical variables
  • It’s called a contingency table because it can tell us how cases are distributed along each variable contingent (or conditional) on one or more categories of the other variable
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11
Q

What is Statistics?

A
  • Statistics is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data
  • Can be applied to questions related to scientific, industrial, social or other settings
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12
Q

What is the process of investigation?

A
  • Identify question/problem
  • Collect relevant data
  • Analyze data
  • Make a conclusion
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13
Q

What is Data in Statistics?

A

Set of observations

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14
Q

What are some examples of Categorical - qualitative data?

A

Factor

Levels - different qualities

Gender, yes/no answer, smoker or not…

Nominal - no inherent order to category
* Religious affiliation, political party…

Ordinal
* Expected or natural order
* Highest education, level of approval - strong–>weak…

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15
Q

What are some examples of Numerical - quantitative data?

A

Take on values that are numbers

Add, subtract, take averages

Continuous:
* Can take on any number

Discrete - count:
* Only non negative counting numbers
* Numbers of votes for a politician

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16
Q

What is meant by a Population?

A

An entire group that you want to draw conclusions about

17
Q

What is Sampling?

A

The selection of a subset of the population of
interest in a research study

18
Q

What is a census?

A

Difficult and expensive way to collect data on the population

19
Q

What is Descriptive Statistics?

A

Organizing and presenting data from a pop/sample
* Presenting data
* Summarizing data

20
Q

What is Inferential statistics?

A

Making conclusions about population based on data from a sample
* Estimating it.
* Hypothesis testing

21
Q

What is Parameter notation?

A

a. Statistic is a numerical summary based on a sample
b. Parameter - numerical summary of a population
c. Keep track of sample vs. census/population
d. Lower case n for sample, N for population
e. Sample statistics usually latin
f. Population usually greek

22
Q

What is Anecdotal evidence?

A

a. Evidence based on a very limited sample size that is not representative
b. Usually composed of odd cases

23
Q

What is a Study Design?

A

Process of investigation
* Identify
* Collect data
* Analyze data
* Draw conclusion

24
Q

Explain Observational Data collection.

A
  1. Cross sectional
    a. Data collected at one point in time on a set of individuals
  2. Longitudinal
    a. Data collected over time on same individuals
  3. No attempt to intervene
  4. Typically cannot prove cause and effect
  5. Survey is typical observational study
  6. Careful about interpreting results
  7. Can always be confounding or lurking variables
    a. Variable not included in study that has an effect on variables studied
25
Q

Explain Experimental Data collection.

A
  1. Apply some type of intervention
  2. Treatment and control groups
  3. Try to remove effect of known confounders
  4. Randomized controlled trials
26
Q

What are Quantative variables?

A
  • Also referred to as numerical variables
  • Variables whose values result from counting or measuring something.
  • Mnemonic: Quantative variables relate to quantity.
27
Q

What are Qualitative variables?

A
  • Also referred to as categorical variables
  • Variables where the values do not result from measuring or counting
  • Also referred to as a factor, with the values within as levels
    Example: “The factor ‘Treatment_Type’ has the levels ‘Placebo’, ‘Exis=ng_Drug’, and ‘Experimental_Drug”
28
Q

What is a discrete variable?

A

A variable whose value is obtained by counting. For Example:
* Number of people who visited the ER
* Number of marbles in a jar
* Number of home runs in a baseball game
* Number of questions answered correctly on an exam

29
Q

What is a continuous variable?

A

A variable whose value is obtained by measuring. For Example:
* Age
* Height
* Weight
* Time required to complete a task
* Speed of a motor vehicle

30
Q

What is a sample?

A

A group of people, objects, or items that are taken from a larger population for measurement

31
Q

What is statistical inference?

A

The procedure through which inferences about a population are made based on certain characteristics calculated from a sample of data drawn from that population

HES Stat E-100 (1 decks)

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