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1. To help understand the common use of statistics in our daily lives
2. To be able to read and understand scientific articles and conduct research in the social and behavioral sciences |
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| refers to the fact that the score measurement values obtained in a study differ from one another, even when all the subjects in the study are asssesed under the same circumstances |
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| Factors that influence scores of performance and that are associated with how measurements are made |
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| The study of methods for describing and interpreting quantitative information, which is called DATA |
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| Refers to procedures for organizing, summarizing, and describing data |
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| Includes methods of making inferences about a larger group of individuals on the basis of data actually collected on a much smaller group |
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| All of the available number of indiivduals being studied |
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| Quanitification of a "likelihood"; assigned a number ranging from 1.00 = complete certainty to 0.00 (impossible) |
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| The orderly assignment of a numerical value to a characteristic |
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The ordered set of possible numbers that may be obtained by the measurement process
Properties Include:
1. Magnitude
2. Equal Intervals
3. Absolute Zero |
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| One instance of the attribute being measured can be judged greater than, less than, or equal to another instance of the attribute |
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| A value which indicates that nothing at all of the attribute being measured exists |
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| Any scale of measurement posessing magnitude, equal intervals, and an absolute zero point |
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Possesses the properties of magnitude and equal intervals but not an absolute zero point
Example: Farenheight or Celcius |
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Results from the classification of items into mutually exclusive groups that do not bear any magnitude relationship to one another
Example: Political Party affiliation, numbers on the back of a football player's jersey, etc... |
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Reflects only magnitude and does not possess the properties of equal intervals or an absolute zero point
Example: "bmw better than a porsche", "bubble gum A sweeter than bubble gum B" |
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Quantity that doesn't change in value within a given context
Ex; Pie (math 3.14....) temp of boiling water 212F, etc... |
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| 1, 2, 3, 4 children not 1 and 1/2 |
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| Weight, temperature, volume, etc.... |
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| Measurement of 1/2 Unit above and one half measurement unit below that number |
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Lecture Notes 1/15/14
Now Forward |
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A. Observation and Question
B. Hypothesis: something that can be verified
C. Experiment
1. Independent Variable: Difference between groups that exists prior to measuring characteristic of interest
2. Dependent Variable: characteristic of interest/ underlying property (thing being measured)
a. Underlying Property (characteristic)
b. Operational Definition: Specification of how we are going to measure underlying property. Determines which statistics you are able to use in underlying data
c. Measurement Scale: set of possible values that can be obtained by the active measurement
D. Observation/Data Collection
E. Analysis statistics
F. Drawing Conclusions
G. Communication
(Look at notes/ Table from class)
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1. Magnitude
2. Absolute Zero
2. Equal Intervals |
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4 types of Measurement Scale
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1. Ratio
2. Interval
3. Ordinal
4. Nominal |
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Order of Operations
(PEMDAS)
Parantheses, Exponent, Multiplication, Division, Addition, Subtraction |
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| Make sure you understand order of operations |
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*Report to 3 decimal places*
Creating the table
1. Begin with X from top to bottom, biggest value to smallest
2. Next frequency (amount of times they show up in the data) *should always add up to N*
3. Next relative frequency (Ex; out of 33 scores, 9 of them are a value of 10, so you take 9/33=0.273
4. Next Cumulative Frequency: start from bottom to top; add the frequency of Xs as you go up. Top should equal N.
5. Cumulative Relative Frequency: Crf: lists the proportion or % of scores at each X or lower |
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| Instructions for Graphing |
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1. Title
2. Axis Tables
3. Mark of axes with equal intervals
4. Graph
a. Histogram: make a bar centered at each X, with a height=frequent measure for X if scale has magnitude, bars should touch!
b. Polygon: Plot points (X, freq measures for that X) and connect w/ straight lines |
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| Descriptive Statistics (3 types) |
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1. Central Tendency
2. Variability
3. Skew |
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1. Mode, Mean, Median
2. Indicate: center of distribution, typical score of the middle (i)
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1. Range, Interquartile Range, Variance, Standard Deviation,Skew
2. Indicates: Differences between data values (spread) |
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| Symmetric or lopsided distribution |
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The most frequently occurring score; can have more than one mode in a distribution
(look at notes)
* can be used with any type of measurement scale* |
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Mean, Average, X(bar above), M (in papers)
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The mean is the "balance point" or "center of gravity" of the distribution
*Mean will put both sides at balance"
****Sum of deviations from mean will ALWAYS equal zero******
(To calculate mean one MUST have magnitude + equal intervals; Interval or Ratio Scale) |
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| Theoretically, the mean is th emiddle score for which it is true that half the scores are above that value and half the scores are below that value (MUST BE IN ORDER) Magnitude |
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