Happiness in Marriage Based on Gender Quantitative Research

  1. Preliminary/design

Being happy in a marriage is important, but who tends to be happier in the marriage, a male or female. According to the general social survey (2014) data sets, I will be conducting my research on happiness of marriage to figure out which gender is happier, so my research question is: Does the type of gender one marries affect the happiness of their marriage?

The data sets I’m going to be using for this project is happiness of marriage, the plan is to figure out if gender affects the happiness of their marriage. The type of groups I’ll be using are male and female. Based on the groups being presented, I will figure out the happiness of a male and female. The method of sampling being used is probability sampling, and the method being used is random sampling. The type of data collection I will be doing is quantitative data analysis. The size of my study would be 2 individuals, a male and female

The Independent variable I will be using is gender, the dependent variable is happiness of their marriage. Type of gender would be coded as, 1= Male (nominal) and 2= Female (nominal), and happiness of marriage would be measured as (Scale), 1=Very happy, 2=Pretty happy, 3=Not too happy, and 4=N/A. I will not be recoding any of my variables

 

Univariate Analysis

Independent Variable: Gender

 

Frequencies

 

Statistics
GENDER OF 1ST PERSON
N Valid 2538
Missing 0
Mean 1.44
Median 1.00
Mode 1
Std. Deviation .496
Minimum 1
Maximum 2

 

GENDER OF 1ST PERSON
  Frequency Percent Valid Percent Cumulative Percent
Valid MALE 1431 56.4 56.4 56.4
FEMALE 1107 43.6 43.6 100.0
Total 2538 100.0 100.0  

 

 

 

 

I was able to compute the variable by using frequencies in SPSS, which reports frequency counts (the number of cases with each unique value of a variable) and the percentages for the selected variable. Aside from that, frequencies can help us see the results in a histogram or bar charts. I attained the tables by entering the independent variable, which is ‘gender of 1st person.’ After inputting the variable in SPSS using the frequency function, I attained a mean of 1.44, median 1.00, and mode of 1. The standard deviation of the variable was .496. The maximum was 2 and minimum was 1. The amount of cases in the variable was n=2,538. The amount of missing cases was 0. According to the variable ‘gender of 1st person,’ I noticed the Histogram displayed more males than females, which tells us there is more males than females. The frequency count for male was 1431 and female was 1107. The amount of people in a specific location was articulated at 1.44 in the Histogram. This allows us to conclude that there are more males than females in the variable ‘gender of 1st person.’

 

Dependent Variable: Happiness of marriage

Frequencies

 

 

Statistics
HAPPINESS OF MARRIAGE
N Valid 1155
Missing 1383
Mean 1.44
Median 1.00
Mode 1
Std. Deviation .560
Minimum 1
Maximum 3

 

 

HAPPINESS OF MARRIAGE
  Frequency Percent Valid Percent Cumulative Percent
Valid VERY HAPPY 691 27.2 59.8 59.8
PRETTY HAPPY 425 16.7 36.8 96.6
NOT TOO HAPPY 39 1.5 3.4 100.0
Total 1155 45.5 100.0  
Missing IAP 1376 54.2    
DK 2 .1    
NA 5 .2    
Total 1383 54.5    
Total 2538 100.0    

 

I was able to compute the variable by using frequencies in SPSS, which reports frequency counts (the number of cases with each unique value of a variable) and the percentages for the selected variable. Aside from that, frequencies can help us see the results in a histogram or bar charts. I attained the tables by entering the independent variable, which is ‘happiness of marriage.’ After inputting the variable in SPSS using the frequency function, I attained a mean of 1.44, median 1.00, and mode of 1. The standard deviation of the variable was .560. The maximum was 3 and minimum was 1. The amount of cases in the variable was n= 1,155. The amount of missing cases was 1,383 According to the variable ‘happiness of marriage,’ I noticed the histogram displayed more people being happy than not happy. The amount of people in a specific location was articulated at 1.44 in the Histogram. The frequency count for very happy was 691, pretty happy 425, and not too happy 39. This allows us to conclude that variable ‘happiness of marriage’ has more happy individuals than not too happy.

 

 

Bivariate Analysis

 

T-Test

 

 

Group Statistics
  GENDER OF 1ST PERSON N Mean Std. Deviation Std. Error Mean
HAPPINESS OF MARRIAGE MALE 817 1.40 .547 .019
FEMALE 338 1.51 .583 .032

 

Using T-test, is going to help us determine whether the difference between means of two groups is due to the independent variable, or if the difference is due to chance. Thus, this procedure allows us to reject or retain the null hypothesis.

The first table shows the mean of variable ‘happiness of marriage’ and ‘gender’. The mean for male is 1.40 and female 1.51. The standard deviation for male is .547 and female is .583, but we cannot conclude if there is a significant difference. The second table, which is the Independent sample test, is going to help is determine the significance between ‘gender’ and ‘happiness of marriage’.

The second table has a column labeled Levene’s Test for Equality of Variance, which provides assumptions of the t-test, based on the variables ‘happiness of marriage’ and ‘gender.’ The sig is .003, which is less than .05. Thus, we are going assume the two groups are significantly different, so we are going to use the equal variances not assumed row. To determine the happiness of marriage between male and females is significant, we have to look at the t-test for equality of means. Looking at the equal variance not assumed row, we see a t value of .003. The Sig.(2-tailed) column in the (p=.003) is less than .05, meaning that there is a statistically significant correlation between variables ‘happiness of marriage’ and ‘gender.’ We can conclude that females are happier in a marriage.

 

Multivariate Analysis

 

Regression

 

Variables Entered/Removeda
Model Variables Entered Variables Removed Method
1 White race household, R WAS LAID OFF MAIN JOB LAST YEAR, GENDER OF 1ST PERSONb . Enter
a. Dependent Variable: HAPPINESS OF MARRIAGE
b. All requested variables entered.

 

 

Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .114a .013 .008 .559
a. Predictors: (Constant), White race household, R WAS LAID OFF MAIN JOB LAST YEAR, GENDER OF 1ST PERSON

 

 

 

ANOVAa
Model Sum of Squares df Mean Square F Sig.
1 Regression 2.403 3 .801 2.563 .054b
Residual 182.514 584 .313    
Total 184.917 587      
a. Dependent Variable: HAPPINESS OF MARRIAGE
b. Predictors: (Constant), White race household, R WAS LAID OFF MAIN JOB LAST YEAR, GENDER OF 1ST PERSON

 

 

The model summary table gives us the response of R square=.013, we can say that the model explains 13% of the variation.

The Anova table gives us the results of the independent variables, we are going to be focused on the value located in the “Sig.” column, because this is the exact significance level of the ANOVA. The value for Sig is .054, which means it does not have significant effects. We are going to reject the hypothesis, and we can conclude that the variables are the same and that multiple regression will not be possible in this case.

In the Coefficient table, it gives us a constant of 1.474, gender of 1st person .103, and R was laid off main job last year -.065, and White race household -.086

Y= 1.474 (constant)+.103 (gender)-.086(White race household) -.065(Laid off)

The coefficient for gender is .103 and it has a positive relationship with happiness of marriage, which means both male and female are happy in a marriage. We can assume that people from a white race household (white or non-white) does not have a significant impact on how happy a person is in a marriage. Moreover, being laid off the main job last year had a coefficient of -.061, and we can assume that being laid off last year does not affect the happiness of marriage.

 

quantitative-research

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Hazel Eyes

Her hazel eyes, this is all I remember seeing. What I cannot forget is her hazel eyes. I dream, think, and see her hazel eyes. Her eyes tell me many things. Her eyes tell me if I’m acting appropriate; they tell me if she is sad; they tell me if she needs more attention. I cannot stop thinking of the first time I noticed her eyes. She was working at Texas; yes, her hazel eyes were far away. But our phone conversations made us closer, which led to video conversations. I took advantage of the moment and began to mesmerize over her hazel eyes. She moved her eyes up and down as my lips moved up and down, I felt like a federal agent was inspecting me. But video chatting was not my high moment. It was seeing her in front of me while I ate my frozen yogurt. As we conversed for hours the sun was fading away, I noticed her hazel eyes changing color. Her eyes were simply beautiful, what can I say, I was sitting with a queen. Until today, I feel lucky to see those hazel eyes. I feel hypnotized……………………giphy

Best Day or Worst Day

Best Day or Worst Day

It all began Christmas, I got a text message on my new Iphone. The first luxuries phone I ever held on my hand. I remember flipping my flip phone open to add new contacts and text people. Man, those were good times. As I slide my finger over my IPhone screen, I can see why people love these phones. They are incredible, the way they function with a touch of a finger, and how it responds within seconds. I click on the green icon on my Iphone that reads “messages.” Its really her, I open the text; I see the following text message: “Hey! What are you doing this Christmas?”, what a surprise, it was really her. My cousin was sitting right beside me; he was laughing at my facial expressions as I read my text message. I responded to her, I said: “I’m chillen with my cousin and family at the apartment complex, do you want to come over and eat?” I turned my phone off and waited. Sitting on this grey couch with small tears on each end of the arms, this is not a pleasant presentation for this girl. My mind began to ramble, it began to process thoughts over thoughts. My thought process felt like the constant movement of race cars going 200 km/h on the Laguna Race Track. Suddenly, I felt something vibrating near my ass, it was a text message, I rushed to slide my iphone screen open, when I suddenly read….

download

Stockton Blvd

Driving down Stockton Blvd on my purple Honda Civic, you can see how dirty my car is compared to others on the street. The hood has small particles of dirt, the window has a spot of shit where a bird missed its target. The pain is slowly fading away like every girl in Stockton Blvd. Yet, the inside of the car is not as bad as the outside of the car. You can see the aluminum foil my girlfriend left by the passenger seat, it contained a tasteful empanada. The empanada is no longer sitting inside the aluminum foil, you know that for sure, it is inside my stomach. People get hungry when they drive 30 minutes, just to see their girlfriend. Yes, that’s how long I drive to see her. I believe it’s worth the drive, to see a beautiful, fun, outgoing girl. Yet, the human beings at Stockton Blvd are not acquiring such love. Reminiscing 2 weeks ago, to the time I noticed a petite woman with a short skirt and  golden heels, and a face of a high school girl helped me remember something. It made me remember my girlfriend, young girls, and female family members. Made me think of how angry, belligerent, and feisty I’ll be if something like this ever happens to the people I love. I was shocked to see her sell herself to the public, the gesture of her hand moving up and down until a car stopped.  I cannot stop thinking of how the public is blind, the public does not see young girls selling themselves. It hurts my heart to see these dehumanizing actions at Stockton Blvd. I wish every woman was saved from their predator, the ugly bastard waiting inside the car while the girl is doing her job. If you ever drive down Stockton Blvd, please inform, advocate, and call the police. These women need help, and I cannot be the only one doing all the work.

to be continued…this has not been edited, it was a quick writing assignment PROSTITUTION

Medication

Medication

Everyone takes a dose of over the counter pills, it could be Tylenol, Aspirin, and Motrin; this is not the case for people who are diagnosed with mental health issues. The drug industry is making billions of dollars each year, the business concentrates on helping individuals with bi-polar, schizophrenia, anxiety, etc. The DSM book contains hundreds of symptoms, which are all treated by medical pills. If companies are making billions of dollars by selling psychic medications, do they know the affects they are delivering to people who take them?

To answer your questions above, it is no. Pharmacies are distributing hundreds of medication pills to homes, residential houses, and hospitals to treat clients. However, how much affect are these pills having on these people? The pills comes in variety of shapes, I can recall from medications I’ve seen over a year at a residential facility; a triangle shape pill, square shape pill, and circle shaped pill. Besides the shape of a pill, a color is added to portray the elegance of the pill. I have seen pink, purple, pink, white, and red pills. The pills also come in different sizes, which include small, medium, and large.  The pills vary in the affects they produce once ingested. As stated by psychcentral.com, the most common side effects include dry mouth, blurred vision and constipation, dizziness, and weight gain. A long term side effect is tardive dyskinesia (a disorder characterized by involuntary movements most often affect the mouth, lips and tongue, and sometimes the trunk or other parts of the body such as arms and legs. If a person continues to take the drugs, the long-term side effects would arise. This can lead to permanent damage.

Dosages: I have seen clients take up to 3 different types of psychic medication. Along with other types of medication; the medication is sometimes taken 1, 2, or 3 times a day. Imagine taking this medication for years, what would happen to you? I’m sure your body would adapt to the amount of medication it is being given; moreover, you are going to need an increase, which leads to a stronger dosage. Does this have you thinking of the long-term effects? This makes me think of my future casket, if I was in a residential facility.

Residential facilities, clinics, and other places are distributing these drugs to their clients; the DSM book is used to articulate the symptom and drug type to treat the client. Psychologytoday.com states, “DSM 5 has neither been able to self-correct nor willing to heed the advice of outsiders. It has instead created a mostly closed shop-circling the wagon and deaf to the repeated and widespread warnings that it would lead to massive misdiagnosis.”  Also,” they have been accused of having a financial conflict of interest because some have (minimal) drug company ties and also because so many of the DSM 5 changes will enhance Pharma profits by adding to our already existing societal overdose of carelessly prescribed psychiatric medicine.” As more money is pour into pharma companies, the expansion of pills is going to continue. The people researching pills are those whom are interested in the field of medicine. However, one can be single minded if they concentrate on one aspect of research. Thus, it causes them to obstruct other means of helping mentally ill people.

Solution: Lets start to incorporate more therapeutic ways of helping these individuals. I’m not saying to stop medicating those who need it, but access those who do not really need medication. This would help reduce the amount of pills being made every day, but it would also help mental health clients live longer and help them find other means of controlling their inner voices.

med

The Homeless Population In San Jose Part 1

Silicon Valley is among the richest area, it is filled with buildings, people, and cars. The buildings are tall and fancy. You can notice the brightness of the windows each time you drive by with your car. Besides the buildings, you can see different types of cars. Let me name a few cars: Honda, Ferrari, Lamborghini, Porsche, Toyota, and other exotic cars. These are just “some” of the cars that make up Silicon Valley. As you travel on the outskirts of Silicon Valley, a tent can be seen far away; the tent belongs to a homeless men. The city of San Jose is being taken over by small tents; the tents are placed everywhere in the city. You can see tents under highway bridges, near neighborhoods, and even on the side walk. This continual problem is causing a risk of drug usage and car invasions.

A continual use of drugs amongst the homeless population is a recipe for disaster. Drugs such as meth, is becoming a huge commodity in San Jose. Because prices of other drugs are rising, the price of meth is dropping. Meth is a white crystalline drug that people can snort, smoke, and inject. The drug allows the individual to create a false sense of happiness, a strong feeling of confidence, and large amounts of energy. This substance is strong enough to addict kids and adults. As the problem of homelessness continues, the city of San Jose is going to suffer with countless arrest; the jails are going to be impacted by minor crimes. These pity arrests can be subsided, if only the homelessness problem in San Jose stops. A solution to the problem is programs for the homeless. I have noticed every person has a specific talent for something. To some it can be cooking, sports, writing, reading, or playing video games. If programs can encourage individuals to use their talent, the person would be motivated to get off the street. If programs motivate people, the large amounts of tents in San Jose would diminish. Focusing on someone’s talent would help with job placements; a person can use their talent to find jobs. Once a job placement has been found, a therapist would be assigned to each homeless individual. The therapist would provide cognitive therapy. Besides single individual therapy, the therapist can focus on large groups. Along with therapy, a person needs a stable home.

San Jose has many empty lots, the lots are not being used; the lots can be used to provide housing for the homeless population. The city of San Jose can ask for funds to build tiny houses. A tiny house can provide enough space for someone to sleep and cook. The tiny houses are cheap and can be placed anywhere. The city can arrange different sectors of lots to different needs of people. For example, a lot can be for individuals that are not able to work, another lot can be for people that can work but are not able to afford rent in San Jose. A lot would have volunteers, workers, managers, and nurses. Each lot would have 3 different positions. A night shift, mid-day shift, and morning shift; each person in the shift would provide living skills to the homeless. The nurse would provide necessary medication, and the managers would provide support to everyone. The volunteers would provide support to the workers and people living inside the lot. This is just one efficient way to keep the homeless people from relapsing again into the streets.

 

To be continue…

The Heart

Blood is rushing fast; it is rushing too fast; it is hitting my heart too fast. All you can hear is the sound of my heart, boom! boom! the blood slowly making its way down my artery. As the blood amalgamates with oxygen, I take another deep breath

*taking a deep breath*

There it goes again, the blood keeps moving down; I cannot control it; it is intractable, as it continues to move down; my heart is getting tired, I breathe once again

*slowly breaths*

I close my eyes, and slowly let go of it all, the blood begins to slow down. Is it time for me to let it all go, once again?

*breaths again*