Recent orders
Methods
Conformity Study
Student Name
Institution affiliation
MethodsParticipants
For the study, 140 participants among them Florida University students who were not taking the psychology class either in the Fall 2019 or the Spring 2020 were randomly selected. Of the 140 participants, 51.4% (n=72) were male and 48.6% (n=68) were female. Ages of the participants ranged from 18 years to 29 years with an average of 22.16 years (SD=3). The sample population consisted of 45.7% Hispanic (n=64), 25.7% Caucasians (n=36), 20.7%African-Americans (n=29), 5.7%Asian –American (n=8) and 2.1%Native Indians (n=3). (See Appendix 1.)
Materials and Procedures
The participants were informed of the study itself, the risks and benefits that it carried for the students, an overview of the information required and the time required as stipulated in the standardized guidelines for informed consent. The participants had to give their consent verbally after which they were given one of the three research study documents that contained both the primary independent and dependent variables for the study. The document also consisted of five parts, the first part had the Abigail Foster Facebook post, unfortunately the professor while handling the question paper to Abigail he also gave her the answer key and Abigail who was certain she was going to work in spite of working hard used the answers. After she did very well the professor who was to curve the results because most students had not done well changed his mind, the dilemma was with Abigail who was not sure what she should do hence, in search for advice she posted on Facebook. Among the three documents in spite of them having the same scenario the condition under each of them is different, the conditions are; support, oppose and mixed which are various reactions to Abigail’s post.
For the support condition, it outlined eight comments by people who believed that Abigail had done nothing wrong and should accept the grade while putting the blame on the professor who could have been more careful. The second condition oppose, also has eight comments from students who believed that Abigail should admit to her wrongdoing by putting herself in the other students’ shoes. Lastly, the mixed condition has no consensus since among the eight responses some people opposed her actions while others gave her support.
After having read the scenario the participants were then required to proceed with part two of the questionnaire where they were required to rate Abigail’s behavior based on some statements by either agreeing or disagreeing. They were to use an interval scale of 1(strongly disagree) to 6(strongly agree). The statements that participants were to evaluate on Abigail’s behavior included, Abigail’s behavior was wrong, Abigail’s behavior was understandable, Abigail’s behavior was reasonable, Abigail’s behavior was unethical, Abigail’s behavior was immoral, Abigail’s behavior was appropriate, and Abigail’s behavior was unacceptable. (See Appendix 2)
In the third part the participant was to rate various statements on what advice they would offer Abigail, their response if they were in the same situation and their general Abigail’s impression. In regards to the advice, there were three statements, I would advise Abigail to keep silent, I would try to comfort Abigail and I would give Abigail the same advice that her friends gave her. For the other two parts of the sections on the response and impressions the participants have in regards to Abigail’s behavior and their own, the interval scale of 1 (strongly disagree) or 6 (strongly agree) was used. In response to what they would do the participant was given two statements on whether they would confess or keep silent and on Abigail’s impressions it was either she seems warm, moral, sincere, competent, confident, competitive or good-natured. Additionally, the fourth part of the questions contained demographic questions that the participant had the choice of not answering if he or she deemed them private. The questions included gender, age, race, relationship status, whether they were FIU students and whether English was their first language. Lastly, in the fifth part the participant was supposed to give their feedback on whether the advice Abigail was given was either in support of her behavior, opposing it or was more of the both of them, they filled their response by marking an X.
While the study has both dependent and independent variables, our focus was on the dependent variables which are warm-cold scale, either accepting or rejecting what she did and the self-ratings. The main variable was accepting or rejecting that was reliant on the responses the people wrote in relation to her post and the influence they would have on her. We hypothesized that the participants who read the support response were most likely to support her in that she should keep it to herself and take the win, for those who read the opposing comments were most likely to find her guilty and condemn her actions.
Results
Under the survey conditions (support vs. oppose vs. mixed) which were our independent variables and while focusing on the participant’s assessment on Abigail’s behavior based on the responses in their scenarios, we arrived as various results. Those who had the suppose response were 46 which was 32.9%, oppose 45 which was 32.1% and mixed were 49 which was 35%. Just like predicted the participant who had the support responses described Abigail competent, moral, confident, warm and good-natured person. They believed that she deserved her grade hence she did not have to report it to the professor, they also termed her response after she was given the answer key to be appropriate and reasonable hence if there was a person to blame it would have to be the professor. However, those who read the opposing notions on the scenarios termed what Abigail had done to be wrong and that she should have reported, they went ahead to describe her as immoral and unacceptable and unethical of what she had done. They also referred her behavior in a not good way disagreeing with all notions in part three of the question. Those who had missed reactions assessment on Abigail tended to balance with a few agreeing while the others disagreed.
In addition, for the ANOVA test which was our main analysis there was a significant difference in whether our dependent variable on accepting or rejecting Abigail’s behavior had been wrong in relation to the support, oppose and mixed independent valuables, F (2,137) = 4.537, p= .021. The test confirmed that the participant’s assessment would be affected by the response scenario they read. Lastly, the Post Hoc Tests analysis is used to show a significant difference among various groups. From the table, it is evident that there is a statistically significant difference between the reactions by those people who had both suppose and oppose response and those with suppose and mixed response which is (p=0.021) and (p=0.035) respectively while there was no difference with those with oppose and mixed response(p=0.969). Also, this test supported the hypothesis that participants were likely to support Abigail in the support condition (M = 4.2, SD = 0.773), the oppose condition was (M = 3.4 SD = 0.986, and the mixed condition (M = 3.816 SD = 0.727). (See Appendix 3)
Discussion
As earlier predicted that depending on the response the participants read they would influence their view and eventually on how they would make inferences on Abigail have been proved. Participants who read the positive response were in support of Abigail’s actions and termed her behavior as appropriate, these same people too while asked of what they would have done they supported that they would keep quiet. Similarly, those participants who read the opposing responses arrived at the conclusion that Abigail did the wrong thing and that for the sake of her integrity she should have reported the matter. Lastly, there was no major difference in those who got both responses since just as predicted some opposed while others supported Abigail’s decision. However, it is clear that the difference in all those scenarios assessment by the participants was not major this could have been the fact that the participants all have an experience of how some classes can be tough and in the event, they find themselves in such a situation they are bound to make the same decision. Frankly, if the same situations were to happen to those people who opposed Abigail’s decision they are likely to just act the same way because until one faced a similar issue can their real intentions be revealed.
Appendix 1
Gender (1 = M, 2 = F)
Frequency Percent Valid Percent Cumulative Percent
Valid Male 72 51.4 51.4 51.4
Female 68 48.6 48.6 100.0
Total 140 100.0 100.0 Race
Frequency Percent Valid Percent Cumulative Percent
Valid Caucasian 36 25.7 25.7 25.7
Hispanic 64 45.7 45.7 71.4
Native Indian 3 2.1 2.1 73.6
African American 29 20.7 20.7 94.3
Asian American 8 5.7 5.7 100.0
Total 140 100.0 100.0 Age
Frequency Percent Valid Percent Cumulative Percent
Valid 17.00 2 1.4 1.4 1.4
18.00 22 15.7 15.7 17.1
19.00 7 5.0 5.0 22.1
20.00 6 4.3 4.3 26.4
21.00 28 20.0 20.0 46.4
22.00 13 9.3 9.3 55.7
23.00 21 15.0 15.0 70.7
24.00 3 2.1 2.1 72.9
25.00 21 15.0 15.0 87.9
26.00 2 1.4 1.4 89.3
27.00 10 7.1 7.1 96.4
28.00 1 .7 .7 97.1
29.00 4 2.9 2.9 100.0
Total 140 100.0 100.0 Frequency Table
Condition (1 = Support, 2 = Oppose, 3 = Mixed)
Frequency Percent Valid Percent Cumulative Percent
Valid Support 46 32.9 32.9 32.9
Oppose 45 32.1 32.1 65.0
Mixed 49 35.0 35.0 100.0
Total 140 100.0 100.0 Appendix 2
Crosstab and Chi Square
Condition (1 = Support, 2 = Oppose, 3 = Mixed) * Part II: Abigail’s behavior was wrong
Crosstab
Count
Part II: Abigail’s behavior was wrong Total
2.00 3.00 4.00 5.00 Condition (1 = Support, 2 = Oppose, 3 = Mixed) Support 3 28 14 1 46
Oppose 7 6 23 9 45
Mixed 4 16 19 10 49
Total 14 50 56 20 140
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 26.198a 6 .000
Likelihood Ratio 29.031 6 .000
Linear-by-Linear Association 5.884 1 .015
N of Valid Cases 140 Condition (1 = Support, 2 = Oppose, 3 = Mixed) * Part II: Abigail’s behavior was understandable
Crosstab
Count
Part II: Abigail’s behavior was understandable Total
2.00 3.00 4.00 5.00 Condition (1 = Support, 2 = Oppose, 3 = Mixed) Support 1 6 19 20 46
Oppose 9 16 13 7 45
Mixed 1 15 25 8 49
Total 11 37 57 35 140
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 29.497a 6 .000
Likelihood Ratio 28.563 6 .000
Linear-by-Linear Association 5.492 1 .019
N of Valid Cases 140 Condition (1 = Support, 2 = Oppose, 3 = Mixed) * Part II: Abigail’s behavior was reasonable
Crosstab
Count
Part II: Abigail’s behavior was reasonable Total
2.00 3.00 4.00 5.00 Condition (1 = Support, 2 = Oppose, 3 = Mixed) Support 3 8 20 15 46
Oppose 10 14 14 7 45
Mixed 1 15 25 8 49
Total 14 37 59 30 140
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 18.740a 6 .005
Likelihood Ratio 18.576 6 .005
Linear-by-Linear Association 1.097 1 .295
N of Valid Cases 140 Condition (1 = Support, 2 = Oppose, 3 = Mixed) * Part II: Abigail’s behavior was unethical
Crosstab
Count
Part II: Abigail’s behavior was unethical Total
2.00 3.00 4.00 5.00 Condition (1 = Support, 2 = Oppose, 3 = Mixed) Support 5 22 15 4 46
Oppose 3 10 21 11 45
Mixed 2 17 22 8 49
Total 10 49 58 23 140
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 10.553a 6 .103
Likelihood Ratio 10.811 6 .094
Linear-by-Linear Association 3.862 1 .049
N of Valid Cases 140 Condition (1 = Support, 2 = Oppose, 3 = Mixed) * Part II: Abigail’s behavior was immoral
Crosstab
Count
Part II: Abigail’s behavior was immoral Total
2.00 3.00 4.00 5.00 Condition (1 = Support, 2 = Oppose, 3 = Mixed) Support 3 20 19 4 46
Oppose 3 10 23 9 45
Mixed 2 12 27 8 49
Total 8 42 69 21 140
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 7.529a 6 .275
Likelihood Ratio 7.498 6 .277
Linear-by-Linear Association 3.760 1 .053
N of Valid Cases 140 Condition (1 = Support, 2 = Oppose, 3 = Mixed) * Part II: Abigail’s behavior was appropriate
Crosstab
Count
Part II: Abigail’s behavior was appropriate Total
2.00 3.00 4.00 5.00 Condition (1 = Support, 2 = Oppose, 3 = Mixed) Support 4 17 14 11 46
Oppose 8 17 13 7 45
Mixed 9 21 15 4 49
Total 21 55 42 22 140
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 5.843a 6 .441
Likelihood Ratio 6.131 6 .409
Linear-by-Linear Association 4.557 1 .033
N of Valid Cases 140 Crosstab
Count
Part II: Abigail’s behavior was unacceptable Total
2.00 3.00 4.00 5.00 Condition (1 = Support, 2 = Oppose, 3 = Mixed) Support 8 23 13 2 46
Oppose 7 15 16 7 45
Mixed 6 19 19 5 49
Total 21 57 48 14 140
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 5.711a 6 .456
Likelihood Ratio 5.908 6 .434
Linear-by-Linear Association 2.328 1 .127
N of Valid Cases 140 Condition (1 = Support, 2 = Oppose, 3 = Mixed) * Part III: I would advise Abigail to keep quiet
Crosstab
Count
Part III: I would advise Abigail to keep quiet Total
2.00 3.00 4.00 5.00 Condition (1 = Support, 2 = Oppose, 3 = Mixed) Support 5 6 19 16 46
Oppose 3 22 15 5 45
Mixed 2 17 24 6 49
Total 10 45 58 27 140
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 20.731a 6 .002
Likelihood Ratio 21.079 6 .002
Linear-by-Linear Association 2.898 1 .089
N of Valid Cases 140 Condition (1 = Support, 2 = Oppose, 3 = Mixed) * Part III: I would try to comfort Abigail
Crosstab
Count
Part III: I would try to comfort Abigail Total
2.00 3.00 4.00 5.00 Condition (1 = Support, 2 = Oppose, 3 = Mixed) Support 0 7 23 16 46
Oppose 2 13 20 10 45
Mixed 0 8 26 15 49
Total 2 28 69 41 140
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 8.488a 6 .204
Likelihood Ratio 8.705 6 .191
Linear-by-Linear Association .092 1 .761
N of Valid Cases 140 Condition (1 = Support, 2 = Oppose, 3 = Mixed) * Part III: I would give Abigail the same advice that her friends gave her
Crosstab
Count
Part III: I would give Abigail the same advice that her friends gave her
2.00 3.00 4.00 5.00
Condition (1 = Support, 2 = Oppose, 3 = Mixed) Support 2 4 24 16
Oppose 3 5 20 17
Mixed 1 10 27 11
Total 6 19 71 44
Crosstab
Count
Total
Condition (1 = Support, 2 = Oppose, 3 = Mixed) Support 46
Oppose 45
Mixed 49
Total 140
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 6.419a 6 .378
Likelihood Ratio 6.485 6 .371
Linear-by-Linear Association 1.469 1 .225
N of Valid Cases 140 Condition (1 = Support, 2 = Oppose, 3 = Mixed) * Part III: If I received the answers, I would keep silent
Crosstab
Count
Part III: If I received the answers, I would keep silent Total
2.00 3.00 4.00 5.00 Condition (1 = Support, 2 = Oppose, 3 = Mixed) Support 11 4 14 17 46
Oppose 18 9 14 4 45
Mixed 14 3 17 15 49
Total 43 16 45 36 140
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 14.258a 6 .027
Likelihood Ratio 15.338 6 .018
Linear-by-Linear Association .237 1 .627
N of Valid Cases 140 Crosstab
Count
Part III: If I received the answers, I would confess Total
2.00 3.00 4.00 5.00 Condition (1 = Support, 2 = Oppose, 3 = Mixed) Support 21 10 8 7 46
Oppose 11 10 6 18 45
Mixed 22 9 5 13 49
Total 54 29 19 38 140
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 9.701a 6 .138
Likelihood Ratio 10.103 6 .120
Linear-by-Linear Association .349 1 .555
N of Valid Cases 140 Condition (1 = Support, 2 = Oppose, 3 = Mixed) * Part III: Abigail seems warm
Crosstab
Count
Part III: Abigail seems warm Total
2.00 3.00 4.00 5.00 Condition (1 = Support, 2 = Oppose, 3 = Mixed) Support 3 5 21 17 46
Oppose 9 7 10 19 45
Mixed 6 3 20 20 49
Total 18 15 51 56 140
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 9.182a 6 .164
Likelihood Ratio 9.616 6 .142
Linear-by-Linear Association .013 1 .911
N of Valid Cases 140 Condition (1 = Support, 2 = Oppose, 3 = Mixed) * Part III: Abigail seems good-natured
Crosstab
Count
Part III: Abigail seems good-natured Total
2.00 3.00 4.00 5.00 Condition (1 = Support, 2 = Oppose, 3 = Mixed) Support 0 6 24 16 46
Oppose 6 10 12 17 45
Mixed 1 6 23 19 49
Total 7 22 59 52 140
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 15.237a 6 .018
Likelihood Ratio 16.012 6 .014
Linear-by-Linear Association .006 1 .937
N of Valid Cases 140 Condition (1 = Support, 2 = Oppose, 3 = Mixed) * Part III: Abigail seems confident
Crosstab
Count
Part III: Abigail seems confident Total
2.00 3.00 4.00 5.00 Condition (1 = Support, 2 = Oppose, 3 = Mixed) Support 22 9 9 6 46
Oppose 28 10 4 3 45
Mixed 32 9 4 4 49
Total 82 28 17 13 140
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 5.786a 6 .448
Likelihood Ratio 5.586 6 .471
Linear-by-Linear Association 3.447 1 .063
N of Valid Cases 140 Crosstab
Count
Part III: Abigail seems competitive Total
2.00 3.00 4.00 5.00 Condition (1 = Support, 2 = Oppose, 3 = Mixed) Support 5 4 19 18 46
Oppose 12 4 13 16 45
Mixed 4 3 22 20 49
Total 21 11 54 54 140
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 8.288a 6 .218
Likelihood Ratio 7.966 6 .241
Linear-by-Linear Association .244 1 .622
N of Valid Cases 140 Crosstab
Count
Part III: Abigail seems sincere Total
2.00 3.00 4.00 5.00 Condition (1 = Support, 2 = Oppose, 3 = Mixed) Support 0 0 15 31 46
Oppose 1 2 11 31 45
Mixed 7 5 13 24 49
Total 8 7 39 86 140
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 17.373a 6 .008
Likelihood Ratio 20.162 6 .003
Linear-by-Linear Association 11.332 1 .001
N of Valid Cases 140 Condition (1 = Support, 2 = Oppose, 3 = Mixed) * Part III: Abigail seems moral
Crosstab
Count
Part III: Abigail seems moral Total
2.00 3.00 4.00 5.00 Condition (1 = Support, 2 = Oppose, 3 = Mixed) Support 10 7 14 15 46
Oppose 25 12 8 0 45
Mixed 24 8 14 3 49
Total 59 27 36 18 140
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 32.026a 6 .000
Likelihood Ratio 34.821 6 .000
Linear-by-Linear Association 12.940 1 .000
N of Valid Cases 140 Condition (1 = Support, 2 = Oppose, 3 = Mixed) * Part III: Abigail seems competent
Crosstab
Count
Part III: Abigail seems competent Total
2.00 3.00 4.00 5.00 Condition (1 = Support, 2 = Oppose, 3 = Mixed) Support 24 9 7 6 46
Oppose 29 8 6 2 45
Mixed 32 10 4 3 49
Total 85 27 17 11 140
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 4.392a 6 .624
Likelihood Ratio 4.347 6 .630
Linear-by-Linear Association 2.869 1 .090
N of Valid Cases 140 Appendix 3
Descriptive
Part II: Abigail’s behavior was wrong
N Mean Std. Deviation Std. Error 95% Confidence Interval for Mean
Lower Bound Upper Bound
Support 46 3.2826 .62050 .09149 3.0983 3.4669
Oppose 45 3.7556 .95716 .14269 3.4680 4.0431
Mixed 49 3.7143 .88976 .12711 3.4587 3.9699
Total 140 3.5857 .85651 .07239 3.4426 3.7288
Descriptive
Part II: Abigail’s behavior was wrong
Minimum Maximum
Support 2.00 5.00
Oppose 2.00 5.00
Mixed 2.00 5.00
Total 2.00 5.00
ANOVA
Part II: Abigail’s behavior was wrong
Sum of Squares df Mean Square F Sig.
Between Groups 6.334 2 3.167 4.537 .012
Within Groups 95.637 137 .698 Total 101.971 139 Post Hoc Tests
Multiple Comparisons
Dependent Variable: Part II: Abigail’s behavior was wrong
Tukey HSD
(I) Condition (1 = Support, 2 = Oppose, 3 = Mixed) (J) Condition (1 = Support, 2 = Oppose, 3 = Mixed) Mean Difference (I-J) Std. Error Sig.
Support Oppose -.47295* .17518 .021
Mixed -.43168* .17153 .035
Oppose Support .47295* .17518 .021
Mixed .04127 .17251 .969
Mixed Support .43168* .17153 .035
Oppose -.04127 .17251 .969
Multiple Comparisons
Dependent Variable: Part II: Abigail’s behavior was wrong
Tukey HSD
(I) Condition (1 = Support, 2 = Oppose, 3 = Mixed) (J) Condition (1 = Support, 2 = Oppose, 3 = Mixed) 95% Confidence Interval
Lower Bound Upper Bound
Support Oppose -.8880 -.0579
Mixed -.8381 -.0252
Oppose Support .0579 .8880
Mixed -.3675 .4500
Mixed Support .0252 .8381
Oppose -.4500 .3675
Descriptive
N Mean Std. Deviation Std. Error 95% Confidence Interval for Mean Minimum Maximum
Lower Bound Upper Bound Part II: Abigail’s behavior was understandable Support 46 4.2609 .77272 .11393 4.0314 4.4903 2.00 5.00
Oppose 45 3.4000 .98627 .14702 3.1037 3.6963 2.00 5.00
Mixed 49 3.8163 .72668 .10381 3.6076 4.0251 2.00 5.00
Total 140 3.8286 .89718 .07583 3.6787 3.9785 2.00 5.00
Post Hoc Tests
Multiple Comparisons
Dependent Variable: Part II: Abigail’s behavior was wrong
Tukey HSD
(I) Condition (1 = Support, 2 = Oppose, 3 = Mixed) (J) Condition (1 = Support, 2 = Oppose, 3 = Mixed) Mean Difference (I-J) Std. Error Sig.
Support Oppose -.47295* .17518 .021
Mixed -.43168* .17153 .035
Oppose Support .47295* .17518 .021
Mixed .04127 .17251 .969
Mixed Support .43168* .17153 .035
Oppose -.04127 .17251 .969
Multiple Comparisons
Dependent Variable: Part II: Abigail’s behavior was wrong
Tukey HSD
(I) Condition (1 = Support, 2 = Oppose, 3 = Mixed) (J) Condition (1 = Support, 2 = Oppose, 3 = Mixed) 95% Confidence Interval
Lower Bound Upper Bound
Support Oppose -.8880 -.0579
Mixed -.8381 -.0252
Oppose Support .0579 .8880
Mixed -.3675 .4500
Mixed Support .0252 .8381
Oppose -.4500 .3675
Tukey HSDa,b
Condition (1 = Support, 2 = Oppose, 3 = Mixed) N Subset for alpha = 0.05
1 2 3
Oppose 45 3.4000 Mixed 49 3.8163 Support 46 4.2609
Sig. 1.000 1.000 1.000
Methods in Research
Methods in Research
Student’s Name
Institution Affiliation
Course Name and Code
Professor’s Name
Date
Methods in Research
Question 1
The term operationalization refers to the process of defining a factor or a concept into a measurable variable. Usually, operationalizing is crucial to a research study because it assists in the creation of research methodology. Once variables are operationalized in the study, the researcher can easily examine the relationship between them and define whether and how variation in one of the variables of interest may result in variation in the other.
A variable refers to something that has the potential to have more than one value or meaning, such as a number. For instance, age can be expressed in different years or months. There are two main different types of variables: independent and dependent variables. The most important difference between these two variables is that an independent variable’s value or presence defines the value of other variables, while the dependent variable’s values are determined by an independent variable’s value or presence. In a study examining the impact of virtual learning on student academic performance during the COVID-19 pandemic, the independent variable is virtual learning, while the dependent variable is academic performance. In this example, a student’s academic performance is determined by the adoption of virtual learning.
Question 2
Subjects, also referred to as participants or samples, are the individuals who participate in the study. To select a sample for a study, sampling is performed. Sampling is the procedure of selecting who to take part in the study and is determined by the nature of the research questions and variables in the study. The sampling frame or population is a group of people from whom the researcher selects their study sample. Sampling may take two forms, probability/random sampling and non-probability/purposeful sampling. The main difference between non-probability and probability sampling is that probability sampling gives all subjects in the sampling frame an equal chance of being selected to participate in the study since participants are chosen at random and without researcher bias. On the contrary, in non-probability sampling, all subjects in a sampling frame do not have equal chances of being selected to participate in the study, which is associated with researcher bias. Probability sampling is considered to be more scientifically valid compared to non-probability sampling. An example of random sampling is whereby if the researcher wants to choose ten people out of 100, the researcher will select the 10th person in every group of 10. On the other hand, an example of non-probability sampling is where a researcher chooses only individuals who engage in physical exercises, such as people who go to the gym, when examining the impact of physical exercise on mental health.
Question 3
My currently proposed research question examines how narcissism contributes to antisocial behavior in men. This proposed research question looks at the relationship between narcissism and antisocial behaviors among men. It also has both dependent and independent variables. In this research question, the independent variable is narcissism, while the dependent variable is antisocial behavior.
Question 4
In my currently proposed research question, which examines how narcissism contributes to antisocial behavior in men, I think the subject is to collect data from would-be male students in a US-based university who are above the age of 18 years. The sample frame that I might use to select to solicit these subjects from would be public universities in the US. I believe it will be more realistic to conduct a non-probability sampling for my proposed study because public universities have more male and female students, as well as male students below the age of 18 who would have wanted to participate in this study. Thus, using non-probability sampling will eliminate the chances of selecting these subjects.
major branches of Judaism Today
Name
Course
Tutor
Date
Major branches of Judaism Today
Judaism religion is based on Abrahamic faith, with its origin being the Middle East. The religion was founded by Moses, though the believers trace their belief to Abraham time. The religion currently has over 13 million believers, most of them being in Israel, Germany and United States. The religion is founder on firm belief in one God, with whom Abraham entered a covenant on their behalf, and worshiped in synagogues.
Judaism has several branches today. The Orthodox Judaists believe that Moses was given both written and oral laws at Mount Sinai. The Torah is believed to contain 613 commandments. The believers observe the Jewish laws, but some integrate them with modernity. Some faithful’s however are too strict in their faith, dress uniquely and live in seclusion. The conservative Judaists argue that the Torah was directly transmitted to man via God (The Jewish Outreach Institute, 1). The Torah thus has human elements. While these laws should be adaptive, the true values of Judaism should not change. The Reform Judaism is based on the belief that the writing of the Torah was done by different people before being combined. As such, the Jewish Laws are not binding. The group however observes some Jewish values and ethics. The Reconstructionist Judaism is based on the argument that Judaism is a religion of civilization that is ever evolving. As such, there should be no personalization of the deity. The Torah is thus observed not because it is God given but because of its rich cultural teachings. Lastly, there is the Humanistic Judaism. This branch was founded by Rabbi Sherwin Wine in Michigan in 1960s. It is based on contemporary human life ((The Jewish Outreach Institute, 1). Religion is viewed as a way of life that is devoid of some supernatural authority. Religion should help man to achieve dignity, self-esteem and humanistic values.
Work Cited
The Jewish Outreach Institute. Different denominations (types) of Judaism. Web. <http://www.joi.org/qa/denom.shtml >