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52 Cards in this Set
- Front
- Back
Basic format of a journal article |
1. Abstract 2. Introduction 3. Methods 4. Results 5. Discussion/Conclusion |
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define abstract |
- summarizes article - do not base worth of the article on the abstract
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Introduction |
1. Background - shows relationship between current research and previously published work 2. statement of purpose - the goal of the research 3. Hypotheses - may or may not be specifically stated |
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Method |
1. Participants - description of subjects and how they were obtained 2. Materials/Instruments - things used to study in enough detail that it can be replicated. Reliability and validity included. 3. Procedures - describes what the subject did, where the study took place, the sequence of events and drop out of subjects. |
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Where is the statistical plan located in a journal article |
the end of the methods section or beginning of results. |
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Results |
- statistical information presented as text and/or tables and graphs often using statisitical notation - most critical part of the research article, but often ignored because of lack of statistical knowledge |
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Discussion/Conclusion |
- non-technical interpretation of the results - explanation should focus on the results according to the original purpose of hypothesis - resason may be given for the results of lack of agreement with the hypothesis - suggestion for future research may be given |
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References |
The appendix - questionnaires - visual and graphs |
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Dependent Variable |
- the effects of unknown causes - the even that needs explained in research
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Independent variable |
- suspected cause of the event (DV) usually not know - the variable that is directly manipulated (treatment group) |
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Research hypothesis |
what the research predicts concerning the relationship between the IDV and DV |
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Null Hypothesis |
- statistical prediction concerning the RH but in the null sense - research question is used if no prediction is made |
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Research Problem |
Problem statements - what the research is concerned with |
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Level of measurement |
the relationship of the values that are assigned to the attributes for a variable |
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why is level of measurement important? |
- helps you decided what statistical analysis is appropriate on the values that were assigned - help you decide how to interpret the data from the variable |
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what are the measurement levels |
1. Nominal 2. Ordinal 3. Interval 4. Ratio |
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nominal |
-provides for classification - no order, distance or origin - race, region, name of condition |
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ordinal |
- has order - indicating more or less of a certain quality - no equal intervals between categories - example: the amount of assistance needed to ambulate from maximal to independent rankings - can be ranked but no equal distance |
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example of ordinal |
0 = less than H.S. 1 = some H.S. 2 = H.S. degree 3 = some college 4 = college degree 5 = post college |
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interval |
- real number properties of order and distance but no true origin in zero - equal interval allow for addition and subtraction - multiplication and division do not make sense because there is no true zero - example: temps in fahrenheit |
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ratio |
- order, distance and origin of 0 - + - X / are all possible - example: length, weight, time, Kelvin temperature, ROM |
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non-paremetric |
- nominal or ordinal - ordinal includes ordered categories or ranks |
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parametric |
- Quantity (Interval or Ratio) |
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Range of scores |
tells us would this population be representative of my subjects |
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Mean |
the "center" of the distribution of scores
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Standard Deviation (SD) |
the spread or variability of the scores
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P-value |
the probability of the scores being due to chance alone |
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Qualitative vs. Quantitative |
- Qualitative = Race/Ethnic group - Quantitative = number of deaths (discrete) height and weight (continuous) |
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frequency distribution |
a table that show the values a variable can take and number of observations of each value - if more than 8 or 10 possible values, values are usually combined into class intervals |
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examples of frequency distribution |
number of persons age or age group racial/ethnic group time period |
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stem and leaf displays |
- frequency distribution with no loss of information - score intervals set up on left side (stem) - shows all but last digit of each observation - last digit is the leave of the plot |
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histogram |
- graph of a frequency distribution - columns are always right next to each other - x-axis intervals should be a equal size |
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a chart is a good for what? |
a good way to display with a qualitative aspect (nominal) - examples: race/ethnicity |
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what type of bar graph should be used when names are long? |
horizontal |
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bar chart/graphs |
- horizontal or vertical - vertical bar chart: x axis is a categorical variable or grouping of continuous - bars are separated |
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Pie Charts |
- simple and easily understood way to display relative proportions - use with single variable or small groups of variables. |
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what is the most useful for generally normal distribution |
the arithmetic mean - average or "mean" - most commonly used - sum of all observations divided by number of obersvations |
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median |
- middle of the set of data. - if n is even, middle rank will be between two observations - the mean of those two observations is the median |
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mode |
the value with the most observations - can be helpful when combined with median or mean , to describe the skewness of distribution |
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normal distribution |
bell shaped curve - mean, median and mode are the same in a normal distribution |
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positive skew |
tail is towards positive |
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negative skew |
tail points towards negative end |
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mesokurtic curve |
baseline for comparison. Like normal curve |
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leptokurtic curve |
high peak |
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platykurtic curve |
low peak. larger distribution of scores |
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minimum and maximum value |
shows the boundaries of the data - gives an idea of how spread out the data is - max value - min value |
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Percentiles |
Maximum is 100th percentile. 100% of value lie below the max
median is 50th percentile: 50% of values lie at or below the median |
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box and whiskers plot |
- illustrate the variability of the data as well as the central tendency and the shape of the distribution - line in box = median - box = inter-quartile range representing 50% of scores - whiskers are the smallest and largest values (5th and 95th percentile) - values outside whiskers are outliers |
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outliers |
scores that lie far away from the rest of the data, usually more than 3 SD.
can have interest to inspect data to determine reason for outliers. |
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how much data lies within 1 SD above and below the mean? |
68% |
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how much data lies within 2 SD above and below the mean? |
95%
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how much data lies within 3 SD above and below the mean? |
98% |