My tutor suggests that I operationalise my hypothesis. This would mean making my hypothesis more specific. As you can see, I have used the words exc

ADDITIONAL:

My tutor suggests that I operationalise my hypothesis. This would mean making my hypothesis more specific. As you can see, I have used the words excessive and significant impact say what exactly that means. For example, excessive would mean anything over 2 hours per day according to American Paediatric Society.

Some of the questions in the survey are reverse coded, this needs to be taken into account when analysing the data.

Data needs to be cleansed. Some people have put age ranges that do not fit with the parameters, for example: participants must be between 11-16 years old, some people have put their childs age as 3, and some people have put 2 or more age ranges or none at all. This can be altered to fit, or treated as outliers.

I have included the QR code at the end of this document to access the survey if you need more information.

The hypotheses are H0: There is no significant difference in the emotional well-being and behaviour of adolescents with excessive screen time usage, and H1: There is a significant impact on the behaviour and emotional well-being of adolescents with excessive screen time usage.

It might not be possible to carry out a correlation, I do not know why this is, it was suggested to me by one of my tutors. I would very much like a correlation analysis as well as the multiple linear regression analysis please.

Increased permitted screen time is linked to increased variability in sociability and screen time limitation skills, indicating that excessive screen time may have distinct effects on teenagers.

The study examines the correlation between screen time and negative outcomes such as anxiety, depression, and behavioural issues.

The predictor variable is the amount of screen time spent on the mobile phone, and the criterion variables are behaviour and emotional well-being. The control variables will be socio economic status and parental involvement, and the moderator variables will be age and gender.

Statistical Analysis: Data will be analysed using SPSS 29. Correlation analysis will determine the strength and direction of relationships between variables. Multiple regression analysis will assess the impact of screen time on behaviour and emotional well-being, controlling for confounding variables such as age, gender, and socioeconomic status.

The study should only include people aged between 11 16 year old. Any ages outside of this do not count.

I need the descriptive statistics, including mean age of all participants and standard deviation. I also need mean ages of male and female participants and standard deviation. I need this written as % as well.

For the results

How many actual hours are they spending on devices during the week. How many actual hours on the weekend. How many hours are parents allowing during week, and on weekend. Standard deviation of all of these.

The standardized coefficients () for the predictors in the regression model. THIS IS THEIR TIME ON DEVICES COMPARED WITH THEIR EMOTIONAL AND BEHAVIOURAL SCORES.

Look at the smaller things as well, I would like the general answer: if screen time has effect on behaviour/emotional problems. Also look at it in more detail, so how screen time affected relationship difficulties, or sociability (I used these in my poster presentation) please be creative and use similar examples.

Was the analysis of variance (ANOVA) indicated that the regression model statistically significant? Numbers here, and what it suggests? So I am looking for if their time spent on devices did or did not predict emotional and behavioural problems.

What was the combined effect of the independent variables? What % of the variability was explained? Was the model able or unable to accurately predict or explain a sizable amount of the variability in emotional and behavioural problems?

I ALSO NEED THE SPSS OUTPUTS TO PUT IN MY APPENDICES PLEASE.

Thank you.