Research Methods Statistics Study
Introduction
Loneliness in individuals is being measured in the study using the Revised UCLA Loneliness Scale (RULS). The purpose of the twenty questions used in the RULS is to see the level of loneliness in different people. The population studied was of a sample size of fifteen people. These individuals varied from the ages of 18 and up. Most were married male Caucasians of the middle class. The scores of each respondent are added up and can fall between the ranges of twenty to eighty. Higher scores would indicate that the individual is considered lonelier. This study would be very helpful to social workers because the rates of suicide or self inflicted danger can be associated to the levels of loneliness. Additionally, the most common variables amongst the lonely individuals can be correlated and further studied. Contributing factors to loneliness can also be assumed.
There are studies that suggest age, gender and social status can affect levels of loneliness. This study can discover if there are deviations when it comes to these variables. The respondents’ answers will be scrutinized according to different variables. This way, it would be easy to pinpoint which variables are most likely to score the highest in the loneliness test.
Methods
The sample population used was of fifteen people with the average age range of forty to forty nine years of age. Most of the respondents were married male. The annual household income of the respondents would describe them to be of (on an average) upper middle to middle class citizens. These respondents were either Caucasian or of Latino descent. All of the respondents completed the survey and answered all of the twenty questions. The method used for the statistics study was through a qualitative survey. The results of the survey will be analyzed, relating the possible variables. The survey results were dissected into parts, the scores of the twenty questions were split up into categories according to the level of loneliness found in the respondent. Variables such as age, race, gender, etc. are correlated to the scores of each respondent. Assumptions can be made from the trends within the study. Additional details regarding connections between age and loneliness, gender and loneliness or income and loneliness can be further scrutinized.
The researcher hypothesizes that Caucasian Females above the ages of 30 are more likely to score higher in the loneliness test. P= 0.05 that there is5% chance that the null hypothesis is correct. There are seven females who have taken the test, where five of them are Caucasian. The tests will be seen in a multivariate type analysis.
The descriptive statistics method to be used is the multivariate frequency distributions. This is used since there are a number of variables to be studied. Many surveys utilize this statistical tool in order to find relations between variables. A contingency table can be created to see which gender shows more signs of loneliness.
The respondents did not vary so much in age and in race. The age group was made up mostly of those between the ages 18-29. The demographics in terms of gender were split up well. However, there were not a lot of differences when it came to civil status, race and annual household income. This made the results hard to further study. Not a lot of variables could be used since most of the population sample belonged to certain groups.
The scores for the respondents were quite consistent. There were no major differences in the answers given. Most respondents would have similar answers to a lot of the questions. Only a couple of deviations were seen.
Out of the fifteen respondents, the percentage of males scored higher in the loneliness test. The hypothesis was proven wrong when said that females would most likely score higher in the test. Out of the eight respondents only three females scored above the mean score. However, the females that scored higher in the tests were the top scorers, meaning that they were most likely more lonely.
The scores per age were distributed quite evenly. Only the respondents who were sixty years or older scored below the mean value and have the least chances of being lonely. The respondents who were between the ages fifty and fifty nine had slight deviation, making them more likely to be lonely. However, the differences were not very extreme. This is also proving the null hypothesis correct.
The scores divided by race showed more consistent results where Latinos are less likely to be lonely. They were the race that scored the lowest amongst all that were tested. This proves the hypothesis correct. Out of the two people who were of another race, both scored high in the loneliness test. However, their scores were not very remarkable. Caucasians showed the highest average score in the test, making them more likely to be lonely.
Single people scored evenly in the test. Married people, though scored almost even, showed a higher average in the score. Those who were under another category – only two respondents – showed that they both scored in the higher ranges of the test. It can be said that married people are most likely to score higher in a loneliness test; a factor that was not considered in the hypothesis.
People who had an income of either 31,000-60,999 and 91,000-120,999 were least likely to be lonely. The ones that scored higher fell under the category of 121,000 and up. Both respondents who fell in this category scored remarkably higher than the rest of the sample population.
μ = 54.467, therefore everything above this number is considered closer to loneliness. Only six respondents over the total fifteen had scores higher than the mean. The ranges of the scores were from 48-61. The respondent with the highest score in the survey is believed to be the loneliest one. Other variables from the survey showed that this individual is aged between 50-59, a married Caucasian female with an annual salary of $121,000. The respondent with the lowest loneliness score is over the age of sixty, a married Caucasian female with an annual salary of $91,000.
Most of the respondents felt that they were in tune with people around them. There were only slight deviations found within the respondents. Most of the respondents were Caucasian between the ages of 18-29 and had an average household income of around $61,000. A lot of the respondents answered very positively. A number of the questions answered showed patterns among respondents. The survey did not show a lot of difference within the respondents.
Discussions and Conclusions
A study such as this would definitely be of help in social sciences. There can be a defined level of loneliness where people will be categorized under. This can be developed with a larger mean. If there were more people in the study, a more reliable mean can be described. Additionally, markers can be placed in the scores of people. For example, if someone scores above sixty, this can be considered dangerous, and help is needed right away, or if someone scores above seventy, further studies on the particular individual should be done, and so on.
The survey would have done a lot better if there were more respondents to be studied. The variety of age group could be wider, if the survey is conducted again. Deviations between age and loneliness level can be further studied if there was more of each age group. Gathering data with only a couple or even just one person in a particular age group cannot result in a very descriptive study. The sample size of fifteen may be satisfactory for a small test. However, if a test such as this is used by social workers, a larger sample should be used. More effort should be put into finding variety when it comes to samples.
A total population would be helpful in justifying the population size. This would have also given the data more accuracy in terms of finding results. The margin of error and other statistical tools can be implied if specific populations were targeted and samples were studied.
