SPSS, part 6: Regressions

Regression can be used to predict variables:

  • IV: x axis (predictor)
  • DV: y axis (criterion / outcome)

Analyze -> Regression -> Linear

  •  move variables into corresponding boxes
  • ensure “Method = Enter”
  • in SPSS
    • raw equation: DV = (B [slope] x IV) + constant [intercept]
    • standardised: ZDV = β [beta] x ZIV (standardised variables to Z scores)
    • standardised is a better indicator of strength and measure independent of units
  • in multiple regression (more than one IV) β measures unique effect of IV – no shared variance
  • look in last table for β value (the correlation) and B and constant
  • look in ‘model summary’ table for R2 (proportion of variance explained by all IVs)
  • look in ‘ANOVA’ table for F value (to check if R2 predicts DV better than chance – if F is significant then R2 is better)
  • R2: need to multiply by 100 to get %

 

 

 

SPSS, part 5: Correlations

Bivariate = linear relationship between TWO variables.

Pearson correlation = r = parametric, assume normal distribution (more powerful)

Spearman’s = ρ (rho) = nonparametric ranked data

Analyze -> Correlations -> Bivariate

  • Move variables into box on right
  • Tick “Pearson” or “Spearman”
  • In output look at the 2 numbers that are the same and significant.

Scattergram: to check it’s linear

Graphs -> Legacy Dialogs -> Scatter/Dot

  • Click “Simple Scatter” and move the variables to the axes (it doesn’t matter which one goes where)
  • To get line of best fit, right-click -> edit content -> Elements -> fit line at total

Phi and Cramer’s V = only look at phi (φ) = both variables dichotomous (2 categories)

Analyze -> Descriptive Stats -> Crosstabs

  • Click “Stats” and choose “Phi and Cramer’s V”
  • Click “Cells” and tick “Observed” and “expected”
  • Check how variables are coded because a negative correlation could mean a positive relationship if coded non-intuitively (low numbers = high levels of variable).

SPSS, part 4: Graphs and tables

Chart Builder – doesn’t calculate mean scores for ordinal variables, so you have to change “measure” to “scale”, but it is easier to use quickly.

Graphs -> Legacy Dialogs -> (choose graph)

Simple Bar Chart: tick “summaries of separate variables”

  • Right-click on chart in output, click “Edit content”
  • Can add title (above the chart), footer (below the chart), and change pattern of bars by clicking properties -> double-clicking on the bar -> “fill and border”

Clustered Bar Chart: tick “summaries of groups of cases”

  • Tick what the bars represent (eg mean) and put in the variable
  • Move that variable to “Category axis”
  • Move the variable you want to split the file by to “Define clusters by”

Multiple Line Graph: tick “summaries for groups of cases”

  • Tick what the lines represent (N for frequency/mean) and put in the variable (if mean)
  • Move the variable to “Category axis”
  • Move the variable you want to split the file by to “Define lines by”
  • Can edit in output through right-clicking

Analyze -> Table -> Custom Tables

If trying to find mean of categorical variables, need to change measure to “Scale” in variable view.

  • Move categorical variables to left (rows)
  • Move variables you want to split the file by to top (columns)
  • Click variable on left -> click “Summary stats” at bottom left
  • Change Format to “nnnn” and Decimals to “2”
  • To add SD or anything else: “Summary stats” -> Move SD from “Statistics” box to box on the right
  • Same with cumulative %: Move “Column %”
  • To add Total: Click on the variable you want the total for -> Click “Categories and Totals” at bottom left -> Tick “Total” on right

Categorical Tables: frequencies, so change measure back to “ordinal”

  • Need to use custom tables when splitting files by TWO variables.

Pivot Tables: Put the second splitting variable into the “Layers” box on the right.

  • Can move things around by double-clicking on the table in the output.

Boycotting sexist music

Happy New Year!

Here’s an interesting question that I think may have a range of opinions – should we boycott music/artisits that we deem to have sexist music videos and sexist language?

So many songs include sexist lyrics and videos (mostly sexually objectifying women).  However… they are usually very catchy tunes.  Is it possible to ignore the sexism and just appreciate the music?  I can’t.  I try, but I think it’s impossible – I’ve noticed it too many times that now I check for it in every song.  I stop listening to songs that I deem derogatory because it upsets me.  It upsets me that little boys and girls listen to those songs and that however much they may not notice the lyrics or however much they know that women should not be treated like objects, I feel like the lyrics must enter some part of their brain, and it must be processed somewhere, unconsciously.

It might seem like overreacting, but I can’t stand hearing that he “fucked two bitches before [he] saw you”, or that she doesn’t let herself have a choice: ” When you need that I’mma let you have it”.  I can’t stand hearing that women are passive characters in sexual interaction – men fuck, nail, and screw; women get fucked, get nailed, get screwed.  I’m sick of women being disrespected by being called sluts, whores, bitches etc – it’s highly dehumanising.  As a matter of fact, psychological literature suggests that when people dehumanise others, they are more likely to be violent towards them.

So, I asked my boyfriend to stop listening to this music too.  Or at least to put his headphones in, so I don’t have to suffer it.  He says he doesn’t listen to lyrics, only to the song.  I think they’re both one and the same.

Lois.

PS. On a brighter note – Rizzle Kicks is safe from all derogatory language (I think) so continue to listen to them all you like!  I’m sure there are others too :) I like Alessia Cara at the moment.