1.3 Data recording, analysis and presentation Flashcards
What are the assumptions of parametric tests?
-Populations drawn should be normally distributed
-Variances of populations should be approximately equal
-Should have at least interval or radio data
-Should be no extreme scores
When are non-parametric tests used?
-When assumptions of the parametric tests cannot be fulfilled
-When distributions are non-normal
What are the 5 types of non-parametric tests?
-Mann-Whitney U Test
-Wilcoxon Signed Ranks Test
-Chi-Square
-Binomial Sign Test
-Spearman’s Rho
What is the observed value?
The number produced after the various steps and calculations for a statistical test have been carried out
What is the critical value?
A value taken from a statistical test table, which must be reached in order for results be significant
What are the conditions of use for the Mann Whitney U Test?
-DV produced ordinal or interval data
-Independent Measures design
-Test for a difference
What are the steps for the Mann Whitney test?
- Rank data as whole cohorts of both groups together
- If there are any tied ranks add ranks they would have occupied and divide by how many that will share the rank
- Calculate R1 and R2 (the total of ranks of each group)
- Put R1 or R2 (whichever is smaller) into the formula to get the observed value
- Find the critical value. The observed value should be less than the critical value for significant results
- Write the significance statement
What are the conditions of use for the Wilcoxon signed rank test?
-DV produced ordinal or interval data
-Repeated measured design
-Test for a difference
What are the steps for the Wilcoxon signed ranks test?
- Column A minus column B to calculate the difference
- Remove any with 0 as that means no differences
- Ignore the minus sign and rank the numbers from lowest to highest
- Look at the difference column and count how many positive figures and how many negative figures there are
- Using the least frequent sign, add the rank of those with that sign, this gives the observed value
- Find the critical value. For significant results, the observed value should be less than the critical value
- Write the significance statement
What are the conditions of use for the Chi-square test?
-DV produced nominal type of data
-Independent measures design
-Difference/relationship
What are the steps for the chi-squared test?
- Calculate the totals of each row and column and the grand total from the contingency table
- Calculate the expected frequency
- Apply the formula to each cell (the O is the original value in the cell) and add these all together
- Calculate the degrees of freedom (no of rows minus 1) x (no of columns minus 1)
- Identify the critical value. For significant results, the observed value should be greater than the critical value)
- Write a significance statement
What are the conditions of use of the Binomial sign test?
-DV produces nominal data
-Repeated measures design
-Testing for a difference
What are the steps for the Binomial sign test?
- If the participant’s score for each condition is the same, they are removed
- Minus the second score from the first score and code the positive differences as + and the negative differences as -
- Count the total number of positives and negatives and identify which sign is the least frequent
- The number of the least frequent sign is the observed value
- Identify the critical value and if the observed value is less than the critical, the results are significant
- Write the significance statement
What are the conditions of use for the Spearman’s Rho test?
-Interval/ ordinal data
-Correlation
-test for relationship
What are the steps for the Spearman’s Rho test?
- Rank each co variable separately low to high (lowest = 1st and tied ranks where applicable)
- Difference rank 1 minus rank 2
- Difference squared
- Sum of difference squared column
- Put this into formula
- If r is positive then it is a positive correlation
- Find the critical value and if the OV is greater than the CV, the results are significant
- Write significance statement.
What degree of significance is used in psychology?
5%
What are the levels of measurement?
Ordinal, nominal, and interval
What is nominal data?
Data as totals of named categories
What is ordinal data?
Data as points along a scale, such that the points fall in order but there are not necessarily equal gaps between those points.
What is interval data?
Data as points on a scale that has equal gaps between the points and is widely recognised as a scale of measurement
What are the strengths of nominal data?
-Easy to generate from closed questions, so large amounts of data can be collected quickly, increasing reliability
-Quick to find the mode to assess central tendency
What are the weaknesses of nominal data?
- Without a linear scale, participants may be unable to express degrees of response
-Points are not on a linear scale so medians and means cannot be used to assess central tendency
-Can only use mode as a measure of spread
What are the strengths of ordinal data?
-More informative than nominal data; indicate relative values on a linear scale
-Easy to generate from likert and rating scales
-Points are on a linear scale so a median can be used as well as a mode to assess central tendency
What are the weaknesses of ordinal data?
-As the gaps between the points are only relative, comparisons between participants may be invalid as they may interpret the scale differently
-Gaps between the points are not equal so a mean cannot be used to asses central tendency
What are the strengths of interval data?
-More informative than nominal and ordinal data as the points are directly comparable because all the points are of equal value
-Easy to generate from closed questions
-Points are on a linear scale, with equal gaps between the points so a mean can be used as well as the mode and median to assess central tendency and variance or standard deviation can be used as measures of spread
-Scientific measurements are highly reliable and have an absolute zero baseline