Flashcards
Semester 2 RSM
Cards in this deck (23)
- 1What is a one-tailed hypothesis?A one-tailed directional hypothesis predicts the nature of the effect of the independent variable on the dependent variable.
• E.g.: Adults will correctly recall more words than children. - 2What is a two-tailed hypothesis?A two-tailed non-directional hypothesis predicts that the independent variable will have an effect on the dependent variable, but the direction of the effect is not specified.
E.g.: There will be a difference in how many numbers are correctly recalled by children and adults. - 3What is a null hypothesis?The null hypothesis states that these will be no significant difference in the amount recalled on a Monday morning compared to a Friday afternoon. Any difference will be due to chance or confounding factors.
- 4What is a hypothesis?A hypothesis is a precise, testable statement of what the researchers predict will be the outcome of the study.
- 5What is the IV and DV?The independent variable = what the researcher changes
Dependant variable = what the research measures - 6What is discrete data?Discrete Data can only take certain values.
Example: the number of students in a class (you can't have half a student).
Example: the results of rolling 2 dice:
can only have the values 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 and 12
(counted) - 7What is continuous data?Continuous Data can take any value (within a range)
Examples: A person's height: could be any value (within the range of human heights), not just certain fixed heights
(Measured) - 8What are the pro's and con's of calculating the mean?+ Usually best with large samples
+ Usually most descriptive and representative (but not in all cases).
+ Works best with “normally distributed” data.
- “Extreme” data sets – not representative. Can be skewed to an outlier. - 9What are the pro's and con's of calculating the median?+ Works well with extreme data sets, does not effect “average” – just finds middle answer.
+ Works well alongside the mean.
+ Works best with “skewed data” – not normally distributed.
- Can be tedious for large sets of data - 10What are the pro's and con's of the mode?+ No calculations needed – least effort to work out
- Not always representative of data findings, just most common answer (may be similar to another)
- Possible to have more than one, or none. Best with “nominal data” - 11What are the 3 measures of central tendency?1. Mean
2. Median
3. Mode - 12What are the 4 levels of measurement?1. Nominal
2. Ordinal
3. Interval
4. Ratio
--> NOIR <-- - 13What are nominal scales of measurement?Nominal = “by name”
At the first level, numbers are used to classify data. The names of variables given a numerical value
Ex. If you were carrying out a study looking at differences between males and females. When entering data for comparison, female could be given the value of 1, and male given the value of 2
You would use the mode to describe these sets of data. - 14What are ordinal scales of measurement?Values given to measurements can be ordered
Ex. Shoe sizes – a numerical value is given to shoes to highlight the difference in size (larger number means bigger shoes)
Can be likert scale
Use mode or median - 15What are interval scales of measurement?They have the properties of the previous 2 scales (classified and ordered), but the distance between each interval on the scale are equal right along the scale from the low end to high end
Ex. Temperature – the distance of measurement between 10c and 20c is the same between 90c and 100c.
BUT!! There is no absolute zero! (A temperature of 0c does not mean there is no temperature, and there are minus figures)
Use mean or median - 16What are ratio scales of measurement?Intervals with a true zero point.
Ex. length, weight, height and speed because these can all have zero points (these figures cannot go into minus numbers like temperature, so 0mph literally means 0 speed
Use mean or median - 17What do you report with normally distributed data? What do you report with skewed dataNormal = Mean & S.D
Skewed = Median & Range & IQR - 18what do measures of dispersion show? Name them...They describe how widely the data set is scattered from the average. They measure the “spread” of the data.
1. Range
2. Interquartile Range
3. Standard Deviation - 19What does the range and IQR and SD tell us about our data?1. Range: tells us the value of the distance between outliers at both ends of the distribution
2. IQR: tells us the value of the middle 50% of the distribution
3. The S.D then represents the amount of dispersion the data set as a whole is from the mean ( + takes account of all scores, - can be skewed by outliers) - 20What is the empirical rule?Works from the ‘Empirical Rule’:
- 68% of the data will fall within 1 standard deviation of the mean
- 95% of the data will fall within 2 standard deviations of the mean
- 99.7% of the data will fall within 3 standard deviations of the mean - 21When should you use the Wilcoxon inferential test?-Ordinal, Interval, Ratio LOD
- Repeated measures - 22When should you use the Mann-Whitney U inferential test?- Ordinal, Interval, Ratio LOD
- Independent Measures - 23When should you use the Spearman's Rho inferential test?Tests for a correlation between 2 variables
Tests ordinal level data
Requires related data (pairs/repeated measures design)
Looks at ‘ranks’ of scores
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- Degree Psychology (Research Methods) Flashcards on Semester 2 RSM, created by Molly Macgregor on 18/05/2016.
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- Molly Macgregor
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