Entity relationship diagram example questions for the newlywed

Entity Relationship Diagram (ERD) Tutorial - Part 2

entity relationship diagram example questions for the newlywed

All questions about SQL refer to the SQL2 or SQL3 standard. Question 1. Alice has a Below is an E-R diagram for a database to help Alice out. Provide appropriate . A fragment definition may involve join over two tables. Q4b. Consider the. Creately diagrams can be exported and added to Word, PPT (powerpoint), Excel, Visio or any other document. Use PDF export for high quality prints and SVG. Compare your practice test results with the performance of those who took the . The questions in the Psychology Test are drawn from relationships, applying principles, drawing conclusions .. bounded entities that take up space and .. Newlyweds Layla and Keith both have normal . (D) Hans Eysenck's trait model.

Although openness also has numerous influences on social and interpersonal phenomena McCrae,we still know little about the effect of openness on the course of intimate and personal relationships McCrae and Costa, Thirdly, previous studies highlight the mutual influences between couples Barelds, ; Kenny and Ledermann, as well as their similarities in personality Gonzaga et al. Personality similarity research often relies on methods that collapse two personality measures into a single score intended to represent similarity.

For example, the female openness score that is higher than the male score may reach the same similarity score because male openness is higher than female openness within each dyad.

Therefore, when we focused on the openness fit, compared to just considering the similarity or dissimilarity, we accounted for various situations of fit in this study. The Interpersonal Aspect of Openness Openness is usually portrayed as an intrapsychic dimension that describes individual differences in the structure and function of the mind McCrae, It is considered a reflection of creativity, artistic interest, emotionality, adventurousness, intellect, and liberal thinking Costa and McCrae, ; Baer et al.

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Openness can further be divided into openness to creative intellect experiences and psychological openness in the motivational, social, and emotional systems McCrae and Sutin, ; Woo et al. In the conceptualization of openness, intrapsychic aspects such as the intellect and perception have been primarily emphasized Deyoung et al. It is better understood as an essential way of approaching the world that affects internal experience, accompanied by interpersonal interactions and social behavior McCrae, That is to say, in addition to the intrapsychic aspects, a consideration of openness in all social fields illustrates a second, interpersonal aspect of openness.

A meta-analytic review also sheds light on the interpersonal domain of openness and illustrated a positive association between openness and interpersonal sensitivity Hall et al. However, the interpersonal aspect of openness has not been well documented Ozer and Benet-Martinez, Openness and Relationship Quality: Individual Approach Past research on the association between individual characteristics and close relationship quality has taken either an individual or a dyadic approach Luo et al.

entity relationship diagram example questions for the newlywed

However, Solomon and Jackson explored that a higher level of openness could not only predict a lower marriage satisfaction but also a higher possibility of dissolution 4 years later. Still other studies based on dating couples illustrated that openness was one of the two most valued personality characteristics by both sexes in the mate-selecting process Botwin et al. As for the partner characteristics, the previous results were inconsistent.

Furthermore, the partner effect might be asymmetrical to the gender. Two other studies showed that individuals who have a mate with a high level of openness are more satisfied with their marriage in newlywed couples Botwin et al. Thus, the effects of openness on the quality of a relationship are still unclear.

There were two competitive hypotheses in the association between personality similarity and relationship quality: The complementary hypothesis suggests that individuals who prefer to seek partners with dissimilar characteristics to achieve novelty and complement will have more communication and individual growth Baxter and West, In the aspect of openness, it is attested that the similarity in openness was associated with greater satisfaction in newlyweds Watson et al.

On the contrary, in the study by Watson et al. In summary, it is still unclear how openness and its consistency interact with relationship quality, leading researchers to conclude it as the only characteristic where no well-documented impact is observed in the interpersonal realm Ozer and Benet-Martinez, Personality similarity research often relies on methods that collapse two personality measures into a single score intended to represent similarity [i.

However, both of these methods have been criticized. In most cases, difference scores are used to represent congruence i. For example, when we use the ADS Turban and Jones, ; Morry, as the similarity index, we cannot distinguish certain situations because the similar high openness dating dyad and similar low openness dating dyad may receive the same scores on similarity indices; on the other hand, the female openness score that is higher than the male score may reach the same similarity score because the male openness is higher than the female openness within each dyad.

What is important is that these similarity patterns may manifest differently in close relationships and cause different consequences, but hardly can they be described by simple difference scores.

Thus, as Griffin et al.

Entity Relationship Diagram (ERD) Tutorial - Part 1

A previous study involving Chinese participants showed that Chinese people scored lower in passion than Westerners, while they did not differ in terms of commitment and intimacy Gao, For the Chinese romantic relationships, the relationship satisfaction was significantly affected by intimacy and commitment, but not by passion Ng and Cheng, Therefore, not surprisingly, dating relationships in Chinese societies seem to involve less hedonic aspiration but a larger degree of relational obligations and mutual respect than those in Western societies Chan et al.

Meanwhile, personality had diverse effects on components of relationship quality. Therefore, it is necessary to distinguish the effect of openness on different components of relationship quality.

The Hypotheses of Current Study To sum up, as an exploratory study, this research aims to clarify openness and its fit effect on several components of couple-level relationship quality among Chinese emerging adults by considering individual and dyadic characteristics simultaneously. We hypothesize at both the individual and dyadic level. At Individual Level Although substantial studies showed weak or even non-correlations between openness and relationship quality regardless of cross-sectional or longitudinal sampling Karney and Bradbury, b ; Watson et al.

The college environment exposes individuals to a diverse set of ideas, people, and cultural traditions, as well as sparks their curiosity and stimulates them to consider a wider range of perspectives and values Robins et al.

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Hence, a college student may benefit from his or her high openness trait in various aspects. Furthermore, there were some research results that indicated that both sexes prefer to choose a mate who scores higher on openness among both dating couples and newlywed couples Botwin et al.

entity relationship diagram example questions for the newlywed

To plot the means for the students and lecturers, select the variable Group from the variable list and drag it into the drop zone for the x-axis. Then add error bars by selecting in the Element Properties dialog box.

The finished chart builder will look like this: The error bar chart will look like this: We can conclude that, on average, students had more friends than lecturers. Access the chart builder and select a simple bar chart. Add error bars by selecting in the Element Properties dialog box. Access the chart builder and select a simple line chart. The x-axis should again be students vs. The error line chart will look like this: We can conclude that, on average, students are slightly less neurotic than lecturers.

Access the chart builder and select a grouped scatterplot. We then need to split the scatterplot by our grouping variable lecturers or studentsso select Group and drag it to the drop zone. The completed chart builder dialog box will look like this: Click on to produce the graph. Then click on in the chart editor to open the properties dialog box. In this dialog box, ask for a linear model to be fitted to the data this should be set by default.

Click on to fit the lines: We can conclude that for lecturers, as neuroticism increases so does alcohol consumption a positive relationshipbut for students the opposite is true, as neuroticism increases alcohol consumption decreases. Note that SPSS has scaled this graph oddly because neither axis starts at zero; as a bit of extra practice, why not edit the two axes so that they start at zero? You can do this by first double-clicking on the x-axis to activate the properties dialog box and then in the custom box set the minimum to be 0 instead of 5.

Repeat this process for the y-axis. The resulting graph will look like this: Access the chart builder and select a scatterplot matrix. We have to drag all three variables into the drop zone. Select the first variable Friends by clicking on it with the mouse.

Now, hold down the Ctrl Cmd on a Mac key on the keyboard and click on a second variable Alcohol. Finally, hold down the Ctrl or Cmd key and click on a third variable Neurotic. Once the three variables are selected, click on any one of them and then drag them into the drop zone. The completed dialog box will look like this: Then click on in the Chart Editor to open the properties dialog box.

Click on to fit the lines. The resulting graph looks like this: We can conclude that there is no relationship flat line between the number of friends and alcohol consumption; there was a negative relationship between how neurotic a person was and their number of friends line slopes downwards ; and there was a slight positive relationship between how neurotic a person was and how much alcohol they drank line slopes upwards.

Reference source not found. To graph these data we need to select a clustered bar chart in the chart builder. Next we need to select Name Condition and drag it into the drop zone.

Finally, we select Participant Sex and drag it into the drop zone.

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The two sexes will now be displayed as different-coloured bars. The graph shows that, on average, males did better on the test than females when using their own name the control but also when using a fake female name. However, for participants who did the test under a fake male name, the women did better than males.

To graph these data we need to select a multiple line chart in the chart builder. In the variable list select the method of teaching variable and drag it into. Then highlight and drag the variable representing score on SPSS homework into.

Next, highlight and drag the grouping variable Sex into. The two groups will now be displayed as different-coloured bars. Additionally, the graph shows that females score higher when the being nice method is used compared to when an electric shock is used, but the opposite is true for males.

This suggests that there may be an interaction effect of sex. In the chart builder double-click on the icon for a simple bar chart, then select the Distance Walked… variable from the variable list and drag it into the drop zone. The x-axis should be the variable by which we want to split the data. To plot the means for males and females, select the variable Participant Sex from the variable list and drag it into the drop zone for the x-axis.

Finally, add error bars to your bar chart by selecting in the Element Properties dialog box. Looking at the graph above, we can see that, on average, females walk longer distances while shopping than males.

Newlyweds, Nuptials, and the Uncomfortable Conversation of Estate Planning

Next we need to do the graph for time spent shopping. In the chart builder double-click on the icon for a simple bar chart. Select the Time Spent … variable from the variable list and drag it into the drop zone. The graph shows that, on average, females spend more time shopping than males. In the chart builder double-click on the icon for a simple bar chart, then select the Love of Animals variable from the variable list and drag it into the drop zone.

To plot the means for males and females, select the variable Type of Animal Wife from the variable list and drag it into the drop zone for the x-axis. The graph shows that the mean love of animals was the same for men married to a goat as for those married to a dog. Next we need to do the graph for life satisfaction. Select the Life Satisfaction variable from the variable list and drag it into the drop zone.

The graph shows that, on average, life satisfaction was higher in men who were married to a dog compared to men who were married to a goat. We then need to split the scatterplot by our grouping variable dogs or goatsso select Type of Animal Wife and drag it to the drop zone. We can conclude that for men married to both goats and dogs, as love of animals increases so does life satisfaction a positive relationship.

However, this relationship is more pronounced for goats than for dogs steeper regression line for goats than for dogs. In the chart builder double-click on the icon for a simple scatterplot. Select the cognitive functioning variable from the variable list and drag it into the drop zone. The horizontal axis should display the independent variable the variable that predicts the outcome variable.

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