SOC305: Researching Society Explain What Main Alternatives Concerning Sampling Strategy - Management Assignment Help

Assignment Task:

Task:

Part B – Long Answer and SPSS Analysis
You should answer all THREE of the following main questions in the spaces provided. The end of the paper is clearly marked. You should spend around 75 minutes on this part of the exam.
Question 1.

• In the box provided, write a statement in around 400 words on the following:
• Explain what main alternatives concerning sampling strategy that social researchers might consider when choosing questionnaires in data collection.
• Question 2(30 Marks)
• You are a researcher who has gathered data from a random sample of 298 questionnaire respondents. With this sample, you are particularly interested in two variables that you have measurements for: Social Grade [grade] and frequency of book reading [bookfreq].
• Social Grade classification, based on occupation, is organized for this research in the following way:
• AB Higher & intermediate managerial, administrative, professional occupations
• C1C2 Supervisory, clerical & junior managerial, administrative, professional occupations, skills manual occupations
• DE Semi-skilled & unskilled manual occupations, unemployed and lowest grade occupations
• Using SPSS, you generate the following frequency table with social grade as the column variable and frequency of book reading as the row variable. Percentages are expressed as totals of the column variable:
• Frequency of Book Reading * Social Grade Crosstabulation
• Social Grade Total
• AB C1C2 DE Frequency of Book Reading Daily Count 34 29 22 85
• % within Social Grade 34.3).3".0(.5%
• At least weekly Count 28 22 20 70
• % within Social Grade 28.3".2 .0#.5%
• Less often Count 24 31 31 86
• % within Social Grade 24.21.31.0(.9%
• Never Count 13 17 27 57
• % within Social Grade 13.1.2'.0.1%
• Total Count 99 99 100 298
• % within Social Grade 100.00.00.00.0%
• Again, using SPSS, you calculate the values chi-square (?2), phi (?), Cramer’s V and gamma (?) for association between the two variables. The results are recorded below:
• Chi-Square Tests
• Value df Asymptotic Significance (2-sided)
• Pearson Chi-Square 10.638a 6 .100
• Likelihood Ratio 10.565 6 .103
• Linear-by-Linear Association 9.145 1 .002
• N of Valid Cases 298 a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 18.94.
• Symmetric Measures
• Value Asymptotic Standard ErroraApproximate Tb Approximate Significance
• Nominal by Nominal Phi .189 .100
• Cramer's V .134 .100
• Ordinal by Ordinal Gamma .214 .069 3.083 .002
• N of Valid Cases 298 a. Not assuming the null hypothesis.
• b. Using the asymptotic standard error assuming the null hypothesis.
• In no more than 300 words in total, in the box below and using the calculations above as appropriate:
• Comment briefly on the strength of association observable between the two variables in the sample and what you interpret to be the direction of causation. (10 Marks)
• Indicate, using appropriate evidence, whether this association between the two variables in the sample is likely to be present in the general population. (10 Marks)
• Drawing on your wider social scientific knowledge, identify and discuss some plausible reasons for the existence of a causal relationship between these variables. (10 Marks)
• Question 3(30 Marks)
• You are a researcher who has gathered data from a random sample of 100 people. The data you have includes measurements of two variables: Age in Years [age] and time, in minutes, spent on social media per day [socmedtime].
• Using SPSS, you create a scatterplot graph for these two variables as below:
•  
• Using SPSS, you calculate Pearson’s r and perform a linear regression with age as the independent variable and time spent on social media as the dependent variable. The SPSS output is recorded below:
• Correlations
• Age in Years Time spend on social media per day
• Age in Years Pearson Correlation 1 -.589**
• Sig. (2-tailed) .000
• N 100 100
• Time spend on social media per day Pearson Correlation -.589** 1
• Sig. (2-tailed) .000 N 100 100
• **. Correlation is significant at the 0.01 level (2-tailed).
• ANOVAaModel Sum of Squares df Mean Square F Sig.
• 1 Regression 255045.000 1 255045.000 51.998 .000b
• Residual 480680.440 98 4904.902 Total 735725.440 99 a. Dependent Variable: Time spend on social media per day
• b. Predictors: (Constant), Age in Years
• CoefficientsaModel Unstandardized Coefficients Standardized Coefficients t Sig.
• B Std. Error Beta 1 (Constant) 226.769 17.623 12.868 .000
• Age in Years -3.364 .467 -.589 -7.211 .000
• a. Dependent Variable: Time spend on social media per day
• We note that the regression equation predicting values for a dependent variable y for values of an independent variable x can be expressed as follows:
• ? = a + bxIn no more than 300 words in total, in the box below and using the information provided above where appropriate:
• Provide some commentary on the strength of association between the two variables and the likely direction of causality. [10 marks]
• Using social scientific reasoning, provide a plausible explanation for the correlation between the two variables. [10 marks]
• Using the appropriate regression equation, calculate how many minutes you would predict someone aged 20 would spend on social media per day (to two decimal places). [5 marks]
• Using the appropriate regression equation, calculate how many minutes you would predict someone aged 80 would spend on social media per day (to two decimal places) [5 marks]
   

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