# PSYC3001 – Tips for Making up Data 心理学 assignment代写

UNSW PSYC3001 – Tips for Making up Data for Assignment 2 – Dr Melanie Gleitzman1Tips for making up data for PSYC3001 Assignment 2 2017You have been asked to make up data for a 3 x 4 design and carry out a planned contrasts analysis in PSY.However, rather than enter your data directly into PSY, it will save you time to use either SPSS or Excel tocreate your data set, because these programs give you greater control over changing the characteristicsof your data to suit your assignment. Whichever you use you will need to import your data, includinggroup coding, into PSY. The SPSS instructions below are for a 2 x 2 design with n = 5 Ps per cell.In order to conveying the impact on data of changing between cells variability and/or within cellsvariability, the discussion below refers to whether data reflect A, B and AB effects. In this case,the SPSS ANOVA summary table is commensurate with PSY output for A, B and AB contrasts for 2x 2 design. [NOTE: Your assignment asks for planned contrasts and not overall tests.]Generating DATA:Step 1: Once you have chosen your factors and levels (and DV), think about the story you want your datato tell. A good place to start with this is to think of what sort AB interaction effect you want your data toshow.

PSYC3001 – Tips for Making up Data 心理学 assignment代写Step 2: Think of a pattern of cell means that will convey your AB interaction effect.Step 3: In SPSS (or Excel), create the variables A, B, GROUP, MEAN, ERROR and input appropriate values. ERROR = within cell individual difference scores (the values above are a ‘quick and easy’ way of injectingindividual difference into a data set).Use COMPUTE to create DV = MEAN + ERROR.A = levels of factor A (1,2). B = levels of factor B (1,2). Note the order of thesevalues indicates whichrows refer to which cells inthe design. eg A = 1, B = 1indicates cell a1b1; A = 1,B = 2 indicates cell a1b2,and so on.GROUP = 1, 2, 3 and 4,corresponding to the 4cells: a1b1, a1b2, a2b1,a2b2, respectively.MEAN = cell mean (youinput whatever values youwant) corresponding tothe 4 cells: a1b1, a1b2,UNSW PSYC3001 – Tips for Making up Data for Assignment 2 – Dr Melanie Gleitzman2For the above data, the Two‐Way ANOVA Summary table indicates B and AB are significant, but not A:Tests of Between-Subjects EffectsDependent Variable: DVSource Sum of Squares df Mean Square F Sig.A 5.000 1 5.000 2.000 .176B 45.000 1 45.000 18.000 .001A * B 125.000 1 125.000 50.000 .000Error 40.000 16 2.500 Corrected Total 215.000 19 Step 4: You may need to modify your data if you do not get the significant effects that you are after.What if your data do not generate the desired significant effects?Now suppose instead of the above cell means, the MEAN values were as below (one‐third the size ofthose above), with the ERROR values the same as above:The Summary Table shows AB significant, but not A or B.Tests of Between-Subjects EffectsDependent Variable: DVSource Sum of Squares df Mean Square F Sig.A .556 1 .556 .222 .644B 5.000 1 5.000 2.000 .176A * B 13.889 1 13.889 5.556 .031Error 40.000 16 2.500 Corrected Total 59.444 19 UNSW PSYC3001 – Tips for Making up Data for Assignment 2 – Dr Melanie Gleitzman3Note that the SSE and MSE is same as first example above. Do you understand why?In this case, the amount of within‐cells individual difference is too large for the between‐cells variation,OR another way of saying this is that the metric of the DV (where cell means vary between 6 and 8.67) isnot appropriate for the metric of the ERROR scores. To inject more between‐cells variation into the data,the pattern of means can be ‘expanded’ as per example 1 above, or the ERROR scores can be contracted(eg halve the ERROR scores]. Halving the ERROR scores (ie values of 1, .5, 0, ‐.5, ‐1 instead of 2, 1, 0 ‐1, ‐2) generates the followingsummary table:Tests of Between-Subjects EffectsDependent Variable: DVSourceType III Sum ofSquares df Mean Square F Sig.A .556 1 .556 .889 .360B 5.000 1 5.000 8.000 .012A * B 13.889 1 13.889 22.222 .000Error 10.000 16 .625 Corrected Total 29.444 19 Note that halving the magnitude of the ERROR scores decreases SSE from 40 to 10. The smaller MSEleads to significant Fs for B and AB.What if your data generate ANOVA Fs that are too large (>100)?The same principles apply as for the above cases, but in the opposite way. Rather than wanting toincrease the spread of cell means or decrease the within‐cells variability you want to do the opposite.If your ANOVA F is too large, this means your ERROR scores are not variable enough for your pattern ofcell means OR your pattern of cell means are too spread out given the within‐cells variability.Either increase your ERROR scores (make them more discrepant from 0, eg 4, 2, 0, ‐2, ‐4), OR decreasethe range of your cell means. To import your data into PSYData must be ordered Group 1 through 4. You can use ‘save as’, and select variables Group and DV, andsave file as .dat. Then copy and paste .dat file into PSY, below heading [DATA], and add your contrasts.Or, copy and past Group and DV columns directly from SPSS into PSY.For J x K designYou can use the above method to give you an indication of whether your data reflect A, B and AB effects.Of course, you will need to run your planned contrasts in PSY to know whether your contrasts aresignificant or not. However, if you find you do need to modify your data (and most students will need todo so), it will be easier to do the modification in SPSS (or Excel), than in PSY.PSYC3001 – Tips for Making up Data 心理学 assignment代写

**PSYC3001 – Tips for Making up Data 心理学 assignment代写**

UNSW PSYC3001 – Tips for Making up Data for Assignment 2 – Dr Melanie Gleitzman1Tips for making up data for PSYC3001 Assignment 2 2017You have been asked to make up data for a 3 x 4 design and carry out a planned contrasts analysis in PSY.However, rather than enter your data directly into PSY, it will save you time to use either SPSS or Excel tocreate your data set, because these programs give you greater control over changing the characteristicsof your data to suit your assignment. Whichever you use you will need to import your data, includinggroup coding, into PSY. The SPSS instructions below are for a 2 x 2 design with n = 5 Ps per cell.In order to conveying the impact on data of changing between cells variability and/or within cellsvariability, the discussion below refers to whether data reflect A, B and AB effects. In this case,the SPSS ANOVA summary table is commensurate with PSY output for A, B and AB contrasts for 2x 2 design. [NOTE: Your assignment asks for planned contrasts and not overall tests.]Generating DATA:Step 1: Once you have chosen your factors and levels (and DV), think about the story you want your datato tell. A good place to start with this is to think of what sort AB interaction effect you want your data toshow.

PSYC3001 – Tips for Making up Data 心理学 assignment代写Step 2: Think of a pattern of cell means that will convey your AB interaction effect.Step 3: In SPSS (or Excel), create the variables A, B, GROUP, MEAN, ERROR and input appropriate values. ERROR = within cell individual difference scores (the values above are a ‘quick and easy’ way of injectingindividual difference into a data set).Use COMPUTE to create DV = MEAN + ERROR.A = levels of factor A (1,2). B = levels of factor B (1,2). Note the order of thesevalues indicates whichrows refer to which cells inthe design. eg A = 1, B = 1indicates cell a1b1; A = 1,B = 2 indicates cell a1b2,and so on.GROUP = 1, 2, 3 and 4,corresponding to the 4cells: a1b1, a1b2, a2b1,a2b2, respectively.MEAN = cell mean (youinput whatever values youwant) corresponding tothe 4 cells: a1b1, a1b2,UNSW PSYC3001 – Tips for Making up Data for Assignment 2 – Dr Melanie Gleitzman2For the above data, the Two‐Way ANOVA Summary table indicates B and AB are significant, but not A:Tests of Between-Subjects EffectsDependent Variable: DVSource Sum of Squares df Mean Square F Sig.A 5.000 1 5.000 2.000 .176B 45.000 1 45.000 18.000 .001A * B 125.000 1 125.000 50.000 .000Error 40.000 16 2.500 Corrected Total 215.000 19 Step 4: You may need to modify your data if you do not get the significant effects that you are after.What if your data do not generate the desired significant effects?Now suppose instead of the above cell means, the MEAN values were as below (one‐third the size ofthose above), with the ERROR values the same as above:The Summary Table shows AB significant, but not A or B.Tests of Between-Subjects EffectsDependent Variable: DVSource Sum of Squares df Mean Square F Sig.A .556 1 .556 .222 .644B 5.000 1 5.000 2.000 .176A * B 13.889 1 13.889 5.556 .031Error 40.000 16 2.500 Corrected Total 59.444 19 UNSW PSYC3001 – Tips for Making up Data for Assignment 2 – Dr Melanie Gleitzman3Note that the SSE and MSE is same as first example above. Do you understand why?In this case, the amount of within‐cells individual difference is too large for the between‐cells variation,OR another way of saying this is that the metric of the DV (where cell means vary between 6 and 8.67) isnot appropriate for the metric of the ERROR scores. To inject more between‐cells variation into the data,the pattern of means can be ‘expanded’ as per example 1 above, or the ERROR scores can be contracted(eg halve the ERROR scores]. Halving the ERROR scores (ie values of 1, .5, 0, ‐.5, ‐1 instead of 2, 1, 0 ‐1, ‐2) generates the followingsummary table:Tests of Between-Subjects EffectsDependent Variable: DVSourceType III Sum ofSquares df Mean Square F Sig.A .556 1 .556 .889 .360B 5.000 1 5.000 8.000 .012A * B 13.889 1 13.889 22.222 .000Error 10.000 16 .625 Corrected Total 29.444 19 Note that halving the magnitude of the ERROR scores decreases SSE from 40 to 10. The smaller MSEleads to significant Fs for B and AB.What if your data generate ANOVA Fs that are too large (>100)?The same principles apply as for the above cases, but in the opposite way. Rather than wanting toincrease the spread of cell means or decrease the within‐cells variability you want to do the opposite.If your ANOVA F is too large, this means your ERROR scores are not variable enough for your pattern ofcell means OR your pattern of cell means are too spread out given the within‐cells variability.Either increase your ERROR scores (make them more discrepant from 0, eg 4, 2, 0, ‐2, ‐4), OR decreasethe range of your cell means. To import your data into PSYData must be ordered Group 1 through 4. You can use ‘save as’, and select variables Group and DV, andsave file as .dat. Then copy and paste .dat file into PSY, below heading [DATA], and add your contrasts.Or, copy and past Group and DV columns directly from SPSS into PSY.For J x K designYou can use the above method to give you an indication of whether your data reflect A, B and AB effects.Of course, you will need to run your planned contrasts in PSY to know whether your contrasts aresignificant or not. However, if you find you do need to modify your data (and most students will need todo so), it will be easier to do the modification in SPSS (or Excel), than in PSY.PSYC3001 – Tips for Making up Data 心理学 assignment代写

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