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research ? tables and figures, levels of measurement, review of basic statistics
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Terms in this set (73)
purpose of tables and figures:
to enhance the readers understanding of the information; should not repeat narrative test but ENHANCE it
tables are:
rows and columns
give a lot of into in a small space
show exact numbers
make comparisons more apparent
anatomy of a table:
table legend
column titles
table body (data)
lines of demarcation
Footnotes
legends are sometimes called...
captions
in a table, the legend goes...
ABOVE the table and to the left
footnotes
used to clarify points in the table, or to convey repetitive information about entries; may also be used to denote statistical differences among groups
figures
graphic illustrations not used in tables
figures include:
charts/graphs
photographs
Drawings (illustrations)
Figures- charts/graphs:
pie
bar
scatter
line
histogram
frequency polygon
figure size rule of thumb:
one-half a page
figures should be what color?
NONE- black and white! (unless doing a presentation)
title on a figure?
no! legend only BELOW THE FIGURE
pie chart
a way of summarizing a set of categorical data or displaying the different values of a given variable (percentage distribution); circle divided into a series of segments and each segment represents a particular category; the area of each segment is the same proportion of a circle as the category is of the total data set; NOMINAL data
bar chart/graph
a chart with rectangular bars with lengths proportional to the values that they represent; used for comparing two or more values that were taken over time or on different conditions, usually on small data sets; bars can be horizontally oriented or vertically oriented; visual display used to compare the amount or frequency of occurrence of different characteristics of data and it is used to compare groups of data
double bar chart
used when we want to represent two sets of data on the same chart; can put the bars side by side or put the bars of one set of data on top of the bars of the other set of data
stem and leaf plot
a display that organizes data to show its shape and distribution; each data value is split into a "stem" and "leaf"; the leaf is usually the last digit of the number and the others digits to the left of the leaf form the stem; provide an "at a glance" tool for specific information in large sets of data
box plot (box and whisker)
a graphic which displays the center portions of the data and some information about the RANGE of the data; there are a number of variations; central box includes the middle 50% of the data; whiskers show range of data; symmetry is indicated by box and whiskers and by location of the mean; easy to compare groups by constructing side-by-side box plots
histogram
frequency distribution graph showing data from interval or ratio scale; bars TOUCH EACH OTHER; touching bars emphasize the continuous nature of the variable; continuous or INTERVAL/RATIO data
histogram: box height=
frequency
histogram: box width=
limits of score
main difference of bar charts and histograms:
-bar charts: each column represents a group defined by a CATEGORICAL variable
-histograms: each column represents a group defined by a CONTINUOUS variable
line graph
continuous data as points and then joins them with a line
frequency polygon
made from a line graph by shading in the area beneath the graph
scatter plots
reveals RELATIONSHIPS or association between two variables
why use graphs?
quick and direct
highlight most important facts
facilitate understanding of data
can convince readers
easily remembered
a good graph:
-accurately shows the facts
-grabs attention
-complements or demonstrates arguments presented in test
-has a title and labels
- is simple and uncluttered
- shows data without altering the message of the data
- clearly shows any trends or differences in the data
- is visually accurate
when is it not appropriate to use a graph?
- data are very dispersed
- too few data (one, two, or three data points)
- data are very numerous
- data show little or no variations
figure= ___ diagram
qualitative
illustration= __
figure
photograph= __
figure
table
legends go above the body of the table and left justified; read from top to bottom; rows and columns
figure
legends go below the graph; read from the bottom up
levels of measurement (data characteristics)
scale that represents a hierarchy of precision on which a variable might be assessed
four levels of measurement:
nominal
ordinal
interval
ratio
nominal
categories- no inherent order
ordinal
category and order
interval
category, order, spacing of equal intervals
ratio
category, order, spacing of equal intervals, zero point
nominal (lowest level of measurement)
-categorical; differ in quality not quantity; qualitative
-assignment of labels
-use numbers to stand for names or categories, but not to represent an intrinsic value
-each observation belongs to its own category
- categories are mutually exclusive (cant be in more than one)
ordinal
-assignment of values along some underlying dimension
-one observation is ranked above or below another
-reflect rankings
- can count and order but not measure
interval
equal distances between points; no true zero point
ratio (highest level- most precise)
-interval scale with a meaningful and non-arbitral zero
- large number of descriptive calculations are possible
- typically, continuous data (open ended questions)
Likert-Type Scales are...
ORDINAL, but are often treated as if they are interval data! These scales do not represent a "measurable quantity"
why do scales of measurement matter?
helps determine the statistical treatment (analysis) of the data
scales of measurement: caution
some criticism; a variable may not conveniently fit into any one of the four classifications; four-level taxonomy is a starting point to be worked with but not to be followed as law
numerical data can be:
discrete data or continuous data
discrete data
can only take certain values; "counted"; ex) number of patients, number of cars
continous data
can take any value within a range; "measured"; ex) height, weight, grip strength
statistics
branch of mathematics in which groups of measurements or observations are studied; "study of mathematics"
data
raw material of statistics
raw data
measurements that have not been organized, summarized or otherwise manipulated
data=
numbers
numbers=
information
purpose of stats
investigate and evaluate the nature and meaning of numerical information
stats field is concerned with:
data
Data:
collection
organization
analysis- testing
summarization- reporting statistics
biostatistics
data analyzed are derived from biological sciences and medicine
sources of data
routinely kept data (charts)
surveys
experiments
external sources (government)
the role of stats in research
- guidelines to summarize and describe data; "rules"
- methods for drawing inferences from groups of subjects to larger groups of people (generalize)
- guidelines for selecting subjects (sampling) and assigning them to groups and collecting data
population (N)
entirety of some group (big)
sample (n)
representative portion of the population (small)
generalizability
when the sample represents the population well, you can draw inferences and conclusions about the entire population from the data gathered
descriptive stats
simply describes data that has been collected
inferential stats
used to make a generalization, estimate, prediction or decision- beyond a simple description
measures of central tendency
mean
median
mode
mean
average
median
"middle" value; best used for ordinal or ranked data or when there are extreme data points present
mode
"most frequent" value; best for qualitative data (nominal or categorical)
measures of variance
range
variance
standard deviation
range
difference in largest and smallest value; "how wide"
variance
dispersion around the mean
standard deviation
average amount of deviation for each score from the mean (square root of variance)
normal distribution
the Bell Shaped Curve
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