__Statistics Project__

Introduction:

This paper focuses on finding out who drinks more coffee in a day whether men or women, the findings are based on the analysis of a sample of 50 individuals where 25 of them are men and 25 are women, the sample was randomly selected and a face to face interview undertaken to collect data. Data was then analysed to determine which group had the highest mean and also to determine what caused the high consumption of coffee in a day.

The research was also determined to find out what causes high levels of coffee per day, some of the factors included cold weather, inactivity and health risks, data collected showed that more people feared to drink more coffee for fear of health risks caused by caffeine in the coffee, however cold weather led to an increase in the consumption of coffee.

Data and methodology:

This study involved the study on the coffee drinking habit on a sample of 25 women and 25 men. The data was collected by means of a face to face interview from the randomly selected sample. The interview was aimed at finding out the gender of the individual, the approximate number of cups consumed per day, whether cold weather increased their level of consumption of the drink, whether respondents feared consuming more coffee due to health risks and whether the respondents consumed more coffee during free time or when not attending work.

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Results:

Data was analysed and the mean number of cups consumed by women and men per day was determined, the following table summarises the total and mean values of the number of cups consumed by both gender:

men

women

total

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95

total

88

mean

3.8

mean

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3.52

mode

3

mode

3

median

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4

median

3

std deviation

1.2909944

std deviation

1.159022577

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variance

1.6666667

variance

1.343333333

The mean number of cups consumed by men amounted to 3.8 with a standard deviation value of 1.290994, for the women the mean value was 3.52 with a standard deviation value equal to

1.159022. the men from the observation of the mean tend to consume more coffee than women and to conclude __this__ results a hypothesis test was performed as follows assuming that the mean value for the men was B1 and that for the women was B2:

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Null hypothesis:

H0: B1 = B2

Alternative hypothesis:

Ha: B1 > B2

We test this hypothesis at the 95% test level

B1–B2

Z calculated = ___________

[(σ12/ n1) + (σ22/ n2)] ½

3.8 – 3.52

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Zcalc = _________________________________

[(1.6666667/ 25) + (1.343333333/ 25)] ½

Therefore Z calculated = 0.8069466

At the 95% test level Z critical = 0.684850

We therefore reject the null hypothesis at the 95% level of test because Z critical is less than the Z calculated, for this reason therefore we can conclude that men consume more coffee than women.

Effect of cold weather on coffee consumption:

There was also an analysis of the cause of increase in the level of coffee consumption. The results included the respondents identifying how they consume coffee during cold weather. The respondents were required to identify whether the strongly agree, agree, neutral, disagree or strongly disagree that cold weather increases the consumption of coffee, this data was then analysed through the use of a scale as follows:

strongly agree

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2

agree

1

neutral

0

disagree

-1

strongly disagree

-2

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Each individual respondents was analysed through this scale, new data series was therefore identified and therefore it was possible to state the dependent variable and the independent variable, the dependent variable in this case was number of cups consumed and the independent variable was data derived from the scale, it was therefore __possible__ to estimate the following model: Y = a + bX

Y = 3.162921348 + 0.5917603 X

Therefore from this estimate it was clear that the autonomous consumption of coffee per day per person is 3.16, further if we hold all other factors constant and there is cold weather then the consumption of coffee will increase by 0.592.

Effect of inactivity and coffee consumption;

The respondents identifying how __they__ consume during their leisure or free time coffee,The respondents in this case were also required to identify whether the strongly agree, agree, neutral, disagree or strongly disagree that inactivity increased the consumption of coffee, this data was also analysed with the following scale

strongly agree

2

agree

1

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neutral

0

disagree

-1

strongly disagree

-2

A new data series was developed and therefore it was possible to state the dependent variable and the independent variable, the dependent variable in this case was number of cups consumed and the independent variable was data derived from the scale depicting inactivity and coffee consumption, it was therefore possible to estimate the following model: Y = a + bX

The results were as follows:

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Y = 3.659056+ 0.015736 X

Therefore from this estimate it was clear that the autonomous consumption of coffee per day per person is 3.659, further if we hold all other factors constant and that an individual is not working then this will increase coffee consumption by 0.01574.

Conclusion:

From the above results therefore it is clear that men consume more coffee than women, this is evident from the hypothesis test that the average number of cups of coffee consumed by men is greater than the average number of cups of coffee consumed by women. Further the research was also aimed at finding out whether there was a relationship between cold weather and an increase in the level of coffee consumed by an individual; from the results it was clear that cold weather influenced coffee consumption. Another analysis of the data collected included determining whether inactivity increased coffee consumption, it was evident that although coffee consumption did not increase as much during periods of inactivity as in the case of cold weather, it was clear that inactivity increased coffee consumption. However there is need for further study regarding coffee consumption and what influences coffee consumption, this can be done **through** selection of a larger sample or even a different sample.

References:

Bluman A. (2000) Elementary Statistics: A Step by Step Approach, McGraw Hill press, New York

D. Bridge (1993) Statistics: An Introduction to Quantitative Economic Research, Rand McNally publishers, Michigan

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