Quantitative and Qualitative Analysis
NAME
, The Quantitative Analysis
A Pearson correlation was carried out to analyse the relationship between young offenders'
attitudes and media avoidance. Before the analysis, checks were made to ensure there was
no outlying data and a normal distribution (see Figure 1).
The histogram (see Figure 2) drawn out for Young Offenders' Attitudes did not present as
symmetrical and also did not offer a bell curve like expected in a Pearson correlation which
assumed a non-normal distribution. This is shown in the Shapiro Wilk statistics (W= .877,
p<.001), as the p-value is less than .05 which is significant for showing abnormality. The Box
plot (see Figure 3) for attitudes showed that there were no outliers in the data, this was also
confirmed by Z-scores where none were higher than 3.29 or less than -3.29.
The histogram (see Figure 4) drawn out for Avoiding Media Consumption also did not
present a symmetrical shape or offer a bell curve. This histogram also showed the data to
have two peaks, this also means there was a non-normal distribution in the data. The
Shapiro-Wilk statistic also showed there was an abnormality for this variable (W=.883,
p=<.001). The box plot (see Figure 5) suggested there was an outlier in the data, however,
the Z-scores did not show outliers or any significant differences in the data. This means no
scores were higher than 3.29 or lower than -3.29.
Descriptive statistics showed the mean score of Young Offenders attitudes to be 3.44 (SD=
1.36) and the mean score of avoiding media consumption to be 3.32 (SD= 1.28). the
correlation between Young Offenders' attitudes and avoiding media consumption is a
moderate positive (r(48)=.421, p=.002) with confidence levels between .161 and .626
suggesting that as attitudes of young offenders increase so does avoiding media
consumption. The r^2 of .171 indicates that avoiding media consumption can explain 17.7%
of attitudes in young offenders.
NAME
, The Quantitative Analysis
A Pearson correlation was carried out to analyse the relationship between young offenders'
attitudes and media avoidance. Before the analysis, checks were made to ensure there was
no outlying data and a normal distribution (see Figure 1).
The histogram (see Figure 2) drawn out for Young Offenders' Attitudes did not present as
symmetrical and also did not offer a bell curve like expected in a Pearson correlation which
assumed a non-normal distribution. This is shown in the Shapiro Wilk statistics (W= .877,
p<.001), as the p-value is less than .05 which is significant for showing abnormality. The Box
plot (see Figure 3) for attitudes showed that there were no outliers in the data, this was also
confirmed by Z-scores where none were higher than 3.29 or less than -3.29.
The histogram (see Figure 4) drawn out for Avoiding Media Consumption also did not
present a symmetrical shape or offer a bell curve. This histogram also showed the data to
have two peaks, this also means there was a non-normal distribution in the data. The
Shapiro-Wilk statistic also showed there was an abnormality for this variable (W=.883,
p=<.001). The box plot (see Figure 5) suggested there was an outlier in the data, however,
the Z-scores did not show outliers or any significant differences in the data. This means no
scores were higher than 3.29 or lower than -3.29.
Descriptive statistics showed the mean score of Young Offenders attitudes to be 3.44 (SD=
1.36) and the mean score of avoiding media consumption to be 3.32 (SD= 1.28). the
correlation between Young Offenders' attitudes and avoiding media consumption is a
moderate positive (r(48)=.421, p=.002) with confidence levels between .161 and .626
suggesting that as attitudes of young offenders increase so does avoiding media
consumption. The r^2 of .171 indicates that avoiding media consumption can explain 17.7%
of attitudes in young offenders.
