Why Do Men Drink More Than Women?
Introduction
The following report outlines the data gathering process, and results into the drinking habits of 18-40 year old male and females over a period of one week in Northern Ireland. The government suggests that people should not drink more than the recommended daily unit guidelines of 3-4 units of alcohol for men and 2-3 units of alcohol for women (attached as Appendix I). They also state that, men should not drink more than 21 standard drinks in a week, and women should not drink more than 14 standard drinks in a week. I is also important to spread them out over the week and to have some alcohol-free days (www.drinkaware.ie), (www.drugalcohol.Info).
Hypothesis
Men drink more than women?
Methodology
Numerical Data …show more content…
Discrete data: can only be a whole number.
Continuous data: this type of data makes up the rest of the numerical data. It can take any value. It is usually associated with some sort of physical measurement e.g. the height of a plant.
For this survey I will use discrete data to prove or disprove my hypotheses.
Data Gathering
A questionnaire was chosen to gather quantitative data on the age of participants and the number of drinks they consume in one week.
Although personal and telephone interviews, observation and electronic surveys are all good methods for gathering qualitative data, there could be a problem with research bias as it is hard to measure the effect the interviewer or observer will have on those being interviewed.
The questionnaire (attached as Appendix II), is a fast and cost effective way of gathering primary data from a lot of people, for my study. However I understand that the quality of data emerging from questionnaires is not always great. The responses to questions are limited because the researcher determines the questions that are asked and the range of answers that can be given. I also cannot predict if the respondent has been truly honest and genuine in their responses (Gillham B. 2007).
Primary data: is where the researcher gathers the information themselves by carrying out a study.
Secondary data: is data that has already been collected from studies that have already been carried out. Resources that are available for secondary data are books, journals and the …show more content…
internet.
Quantitative data: provides information which can be easily analysed statistically and fairly reliable. It is data that is counted or measured.
Qualitative data: is data that is descriptive. it helps to gather peoples’ attitudes and opinions to things.
Sampling types
Random sampling: each member of the population has an equal chance of being selected.
Stratified sampling:
Quota sampling: the researcher decides the criteria needed e.g.
number of men, women, different age groups, to best represent the population.
Convenient sampling: sample chosen on the basis of availability.
Snowball sampling: is useful in hard to reach groups e.g. homeless people. This involves the participants referring the researcher on to others.
A random group of school children will be selected to partake in the filling out of the questionnaire of the relevant age group. The researcher is aware that this is not a true sample of the target population because they will not know the background of the participant (Denscombe M, 2007)
From the original data gathered from 200 participants, I decided to take a random sample of 40 males and 40 females to represent the population to assist in my studies. For my study I plan to compare the ages and drinking habits between the male and the female participants to prove or disprove my hypotheses.
Analysis
Once the raw data was selected, it was tallied and grouped together so that it could be easily analysed. From the age grouped frequency tables I was able to produce a Bar Chart showing the number of participants in each age group and a Histogram showing the frequency density of each
group. Bar chart I
This chart tells us that the largest number of male respondents from the sampling frame were in the youngest group (18-23). The two middle groups included the same number of respondents and the oldest age group (36-41) contained the least number of respondents.
Bar Chart II
We can see from this chart that the first age group had the least number of respondents from the sampling frame, with the second age group containing the largest number of respondents. Bar Chart III
The male percentages were spread across the age groups with 18-23 containing 35% of respondents, 24-29 was represented by 25% of the respondents, 30-35 had also 25% and the 35-41 had the least with only 15%.
The female had 17.5%
Frequency Polygon
Shows on average that males aged ? have a lower consumption rate of alcohol ????????????? From the cumulative frequency tables I was able to find the Mean age group, Modal Group and the Median group for both genders. A frequency polygon was selected for both the male and female participants, plotted against the midpoint of the age groups. Also from these tables I was able to create a Cumulative Frequency Chart (CFC) plotted at the top of each group. From the male CFC we worked out the Q1, Q3 IQR and the median (see chart ?). From the female CFC we also worked out the Q1, Q3 IQR and the median (see chart ?).
Findings
The age of the respondent’s surveyed were between 19 and 40 years old with the measure of averages of: Male Female | Mean: | Mode: | Median |
The grouped tally Chart (on page ?) tells us that while the majority of females drank on average between 10-19 units of alcohol per week (almost half of the female respondents in the study), none of them in the whole study drank more than 29 units of alcohol, unlike the males who were representative in all five unit groups. This lends to my hypotheses that men drink more than women.
The findings from the CFG box plots we can see that the median for the males is 26 with an Interquartile range of 11, and the female median is ? with an Interquartile range of ?.
In the scatter graph we can see that there is no link between the variables with both the male and female respondents showing that there is no correlation between the age of the respondent and the number of units of alcohol they drink.
We can see from the frequency polygon showing both ages of the respondents, at no time was the population represented equally within each age group.
Conclusion
From the research carried out by myself we can see that my hypotheses is proved that “Men drink more than women”.
The following report outlines the data gathering process, and results into the drinking habits of 18-40 year old male and females over a period of one week in Northern Ireland. The government suggests that people should not drink more than the recommended daily unit guidelines of 3-4 units of alcohol for men and 2-3 units of alcohol for women (attached as Appendix I). They also state that, men should not drink more than 21 standard drinks in a week, and women should not drink more than 14 standard drinks in a week. I is also important to spread them out over the week and to have some alcohol-free days (www.drinkaware.ie), (www.drugalcohol.Info).
Hypothesis
Men drink more than women?
Methodology
Numerical Data …show more content…
Discrete data: can only be a whole number.
Continuous data: this type of data makes up the rest of the numerical data. It can take any value. It is usually associated with some sort of physical measurement e.g. the height of a plant.
For this survey I will use discrete data to prove or disprove my hypotheses.
Data Gathering
A questionnaire was chosen to gather quantitative data on the age of participants and the number of drinks they consume in one week.
Although personal and telephone interviews, observation and electronic surveys are all good methods for gathering qualitative data, there could be a problem with research bias as it is hard to measure the effect the interviewer or observer will have on those being interviewed.
The questionnaire (attached as Appendix II), is a fast and cost effective way of gathering primary data from a lot of people, for my study. However I understand that the quality of data emerging from questionnaires is not always great. The responses to questions are limited because the researcher determines the questions that are asked and the range of answers that can be given. I also cannot predict if the respondent has been truly honest and genuine in their responses (Gillham B. 2007).
Primary data: is where the researcher gathers the information themselves by carrying out a study.
Secondary data: is data that has already been collected from studies that have already been carried out. Resources that are available for secondary data are books, journals and the …show more content…
internet.
Quantitative data: provides information which can be easily analysed statistically and fairly reliable. It is data that is counted or measured.
Qualitative data: is data that is descriptive. it helps to gather peoples’ attitudes and opinions to things.
Sampling types
Random sampling: each member of the population has an equal chance of being selected.
Stratified sampling:
Quota sampling: the researcher decides the criteria needed e.g.
number of men, women, different age groups, to best represent the population.
Convenient sampling: sample chosen on the basis of availability.
Snowball sampling: is useful in hard to reach groups e.g. homeless people. This involves the participants referring the researcher on to others.
A random group of school children will be selected to partake in the filling out of the questionnaire of the relevant age group. The researcher is aware that this is not a true sample of the target population because they will not know the background of the participant (Denscombe M, 2007)
From the original data gathered from 200 participants, I decided to take a random sample of 40 males and 40 females to represent the population to assist in my studies. For my study I plan to compare the ages and drinking habits between the male and the female participants to prove or disprove my hypotheses.
Analysis
Once the raw data was selected, it was tallied and grouped together so that it could be easily analysed. From the age grouped frequency tables I was able to produce a Bar Chart showing the number of participants in each age group and a Histogram showing the frequency density of each
group. Bar chart I
This chart tells us that the largest number of male respondents from the sampling frame were in the youngest group (18-23). The two middle groups included the same number of respondents and the oldest age group (36-41) contained the least number of respondents.
Bar Chart II
We can see from this chart that the first age group had the least number of respondents from the sampling frame, with the second age group containing the largest number of respondents. Bar Chart III
The male percentages were spread across the age groups with 18-23 containing 35% of respondents, 24-29 was represented by 25% of the respondents, 30-35 had also 25% and the 35-41 had the least with only 15%.
The female had 17.5%
Frequency Polygon
Shows on average that males aged ? have a lower consumption rate of alcohol ????????????? From the cumulative frequency tables I was able to find the Mean age group, Modal Group and the Median group for both genders. A frequency polygon was selected for both the male and female participants, plotted against the midpoint of the age groups. Also from these tables I was able to create a Cumulative Frequency Chart (CFC) plotted at the top of each group. From the male CFC we worked out the Q1, Q3 IQR and the median (see chart ?). From the female CFC we also worked out the Q1, Q3 IQR and the median (see chart ?).
Findings
The age of the respondent’s surveyed were between 19 and 40 years old with the measure of averages of: Male Female | Mean: | Mode: | Median |
The grouped tally Chart (on page ?) tells us that while the majority of females drank on average between 10-19 units of alcohol per week (almost half of the female respondents in the study), none of them in the whole study drank more than 29 units of alcohol, unlike the males who were representative in all five unit groups. This lends to my hypotheses that men drink more than women.
The findings from the CFG box plots we can see that the median for the males is 26 with an Interquartile range of 11, and the female median is ? with an Interquartile range of ?.
In the scatter graph we can see that there is no link between the variables with both the male and female respondents showing that there is no correlation between the age of the respondent and the number of units of alcohol they drink.
We can see from the frequency polygon showing both ages of the respondents, at no time was the population represented equally within each age group.
Conclusion
From the research carried out by myself we can see that my hypotheses is proved that “Men drink more than women”.