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Answer A) Part A, Section 2:

  1. Null hypothesis (Ho): Saving money by married couples leads to increase in marital satisfaction.

  2. Alternative hypothesis (Ha): Saving money by married couples does not lead to increase in marital satisfaction.

  3. Independent Variable(s): Regular Monetary Savings. The information only suggests that there were couples who either saved money or did not save it. There are therefore no levels in independent variables. The levels of saving amounts are not considered.

  4. Dependent Variable(s): Level of Marital Satisfaction

  5. The research does not take into consideration the following: the economic conditions of the couples, whether the standard of living same in all cases, the number of children and the number of dependents in the family, health of family members, number of pets, the sources of income in the family, whether both the partners are working or there is a single income, types of expenses, amount of income etc. There are a lot of other factors that can have a possible effect on the level of marital satisfaction in tested couples. These factors are not considered so conclusions drawn on the basis of this research are not justified.

  6. The DV is level of marital satisfaction and IV is monetary savings. To make this research experimental, the respondents chosen should be randomly assigned. The next step is to think about the confounding variables which need to be controlled while this experimental research goes on. The confounding variables can be, economic conditions of the selected couples, income sources and amounts, the types of expenses, standard of living, number of children and dependents in the household etc. Now in a controlled experiment the variation in these variables should be minimised or kept constant. The effect of confounding variables on dependent variables should be incorporated.

Answer B) Part B, Section 2:

Results and Discussion:

The measure of central tendency calculated in this case is mean. Variability is calculated with the help of standard deviation. The two tailed t-test has been used to test the null hypotheses at the significance level of (p<0.05). The results are surmised in the table below:

table shows Marks of students in Phonics Group and Control Group

The mean value of marks obtained in case of phonics group is way higher than the control group. This shows that phonics group has performed better than the control group. It is also observed that the standard deviation of control group is higher than that of phonics group. A higher standard deviation shows that the marks are more widely spread. It can be concluded that this performance betterment is due to the treatment (tuition for eight weeks) the respondents were subjected to in phonics group. The value of t-test obtained is 2.42996 and the p value is 0.02178 which is less than 0.05. Thus, in the above case the null hypothesis holds true and so we accept the null hypothesis. The null hypothesis states that daily instructions in phonics would help in the betterment of few aspects of reading ability in children.

Answer C) Part C, Section 2:

The groups in this study are four in number. The treatment groups are E1(Praise), E2(Reprove), E3(Ignorance) and C(Control Group). The statistic that is used to analyse the effect of treatment (Independent Variable) on the performance of the group (Dependent Variable) is one-way Anova. The assumptions for Anova are satisfied and the analysis can be summarised in the following tables. The central tendency is measured by mean, the variability is measured by standard deviation. The one-way Anova is used to find out if there exist significant differnces between means of two or more independent groups. In our case the F-value comes to 102.945 and p value is less than 0.00001(p<0.05). This indicates that the result is significant. This shows that all the means have significant difference and thus the performance of the students is affected by the type of treatment given to them.

table shows Marks of Different Treatment Groups
graph shows Marks of Different Treatment Groups

Post Hoc tests were conducted to find out which group of means had the significant difference. The results show that there was significant difference between the E1 group students and the E2 group students. The value of the static foe Duncan’s Multiple Range test came to 10.15 in this case which was less than the difference of means of these groups. This shows that there was significant difference between them. The value of the static was equal to the mean in case of E2:E3 and E2:E4 groups. For the E3:E4 groups the value was greater than the difference so no significant difference was found.

The above results show that the performance of the students is affected by praise, reprimands, ignorance. The behaviour causes positive and negative impact in the performance of the children. The ones receiving praise started to work hard and performed better and the ones who were reprimanded lost confidence and performed poorly in the tests. The group which was ignored behaved in the same way as the control group because there was neutral or no attention on them so it behaved as if nothing changed for them. This resulted in a similar performance by them as the other students who were kept away from any kind of reinforcement.

Answer D) Part D, Section 2:

The groups in this study are four in number. The treatment groups are at times zero (T0), T1(2 years), T2(4years) and T3(6 years). The statistic that is used to analyse the effect of time(Independent Variable) on the worry expression scale of the group (Dependent Variable) is one-way Anova. The assumptions for Anova are satisfied and the analysis can be summarised in the following tables. The central tendency is measured by mean, the variability is measured by standard deviation. The one-way Anova is used to find out if there exist significant differences between means of two or more independent groups. In our case the F-value comes to 1.93459 and p value is less than 0.137901(p>0.05 level of significance). This indicates that the result is not significant. This shows that the means donot have significant difference and thus the null hypothesis time spent in the marital relationship does not impact the level of expression of worries in respondents.

table shows Worry Expression Scale
graph shows Worry Expression Scale

Post adhoc tests conducted also showed that there is no difference in the means. The above graphs show the data and the variance.

The ANOVA value clearly indicates that time is not affecting the level of expression of worries in married couples. The research design was only based on one variable and that is time. The relationship in couples is affected by a lot of other variables such as the condition of their family financially and economically, the income standards, amount of time spent by the couple together on a regular basis, standard of living, professional life of an individual, compatibility, the number of kids and the number of dependents in the family, standard of living they need to maintain, social life, the ethical and moral standards they follow, health issues and other such factors.

These variables are confounding variables and they should be taken into consideration before the experiment. Not considering them was that flaw in research design of Dr. Feelgood. The impact of these confounding variables should be minimised or kept at a constant level. Also random assignment is necessary in this case. The data relating to confounding variables and the conditions of participant’s history should be collected to know precisely what are the conditions of respondents not expressing their worries. This data should be incorporated in the research to give reliable results.

Remember, at the center of any academic work, lies clarity and evidence. Should you need further assistance, do look up to our Psychology Assignment Help

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