B4 Essay Example | Topics and Well Written Essays - 1000 words

B4 - Essay ExampleOrdinal and interval variables draw measurements. Interval data is actually measured on a continuous scale (actual quantities of some flavour like height or ripen) while ordinal data is numerical form of classification, where whole add up atomic number 18 used to denote order but the numbers themselves argon not measures but a form of classification (GraphPad.com). display board 1 Variables Measured in the Survey Interval variables Ordinal variables vapid variables Age Age category Gender Distance traveled Distance category Reason 1 Regularity of visits Reason 2 Satisfaction with price Department shape of items Purchase Service fee Quality Follow up everywhereall Store Contact The variables in the top row are italicized to indicate that they are independent variables. In this survey, it was hypothesised that demographic factors such as age and gender (pre-existing qualities or independent variables) might influence opinions and behaviour of respondents (d ependent variables). For men and women might differ in the surpass they are prepared to travel to a store. Description of the Data Table 2 shows the number of women and men in the sample and various measures of their age profile. Table 2 Demographics of the Sample Gender All Women Men Number of people 582 373 (64%) 209 (26%) Mean age 42.6 42.8 42.3 Minimum age 17 17 17 Median age 42 42 42 Maximum age 75 75 74 The sample comprises 582 shoppers mingled with the ages of 17 and 75, nearly two-thirds of who are women and just over third men. The age profiles of the men and women are truly similar. Analysis of the distance travelled by respondents to the store where they were interviewed revealed a wide disparity. The modal distance (the most common length or trip) was less than a mile, but many had travelled much further, up to 53 miles. The median distance travelled was 5 miles and the mean just under 10. This indicates a positively skewed distribution where it is difficult to say wh at is the typical distance travelled to the companys stores. inferential Statistics Table 3 shows the results for all shoppers, with men and women grouped separately. Separating womens and mens responses in this demeanor allows a preliminary assessment of whether the independent variable (in this case gender) is influencing the dependent variable (distance travelled to the store). Table 3 Distance Travelled to the Store where Interviewed Distance travelled Less than 1 mile 1-5 miles 5-10 miles 10-30 miles Over 30 miles Total Women 49 (13%) 149 (40%) 83(22%) 69 (19%) 23 (6%) 373 Men 23(11%) 74 (35%) 51 (24%) 52 (25%) 9 (4%) 209 Total 72 223 134 121 32 582 The message is mixed a higher proportion of the women than of the men travelled the shortest distances, but at the other end of the scale women were also more likely than men to open travelled the longest distances. A possible means of determining whether there is a difference amid the distances men and women are prepared to trav el to the companys shops is to compare the mean raw distance (using the actual mileages rather than the categories) travelled by respondents of each gender. The mean distance travelled by the womanly respondents was 9.54 miles compared with 10.26 miles by the men. The standard deviations of the two samples are similar (11.1 and 10.6), so it is appropriate to conduct a eccentric person 2 test, but since the samples are independent and of different sizes we use an independent t-test