## Questions

1 What is meant by data interpretation? Discuss the kinds of pitfall that we have to watch for when interpreting data.

2 Explain data tabulation and editing and coding.

3 Calculate the percentage of house owners across all age groups for the whole sample, using data from Table 10.17.

TABLE 10.17

Number and percentage of house owners among three age groups

TABLE 10.17

Number and percentage of house owners among three age groups

 18-29 (number) 30-49 (number) 50+ (number) Total interviews % house owners 150 230 140 36 65 29

4 Calculate the mean, the median and the mode in the case given in Table 10.18.

4 Calculate the mean, the median and the mode in the case given in Table 10.18.

TABLE 10.18

Cars per household

Number of cars per household in 25 surveyed households

Number of cars per household in 25 surveyed households

Which average best describes the data?

5 What is the range in the data in Question 4?

6 What is the standard deviation and variance of the data in Question 4?

7 In a survey of 281 consumers, the question asked was: Are you aware of brand X? The tally of responses are shown separately for both men and women in Table 10.19.

 Yes No Men Women 55 85 65 76

Is there a difference between men and women in terms of their respective levels of awareness of brand X?

8 What are analysis of variance techniques? What do they attempt to measure? In the context of what kinds of problem might they be useful?

9 Data for 14 brands of cider and their price and alcohol content per glass are shown in Table 10.20.

Cider brands, price and alcohol content per glass

Brand

Price (£)

Alcohol content (%)

1

1.71

3.3

2

1.62

3.2

3

1.94

3.1

4

1.81

3.6

5

1.65

4.3

6

1.67

2.2

7

1.56

3.6

8

1.54

1.8

9

1.76

1.7

10

1.88

2.4

11

1.91

2.1

12

1.93

3.2

13

1.72

3.3

14

1.88

(a) Produce a scattergraph to show the relationship between the two variables.

(b) Calculate the Pearson correlation coefficient to measure the relationship between the two variables.

(c) Calculate the bivariate regression equations (i) using alcohol content as the independent variable and (ii) using the price of cider as the independent variable.

(d) Interpret and comment on the analysis you have undertaken.

10 Table 10.21 is a dataset similar to that in Table 10.8, which refers to a different area of the country. Use multiple regression analysis to analyse the dataset.

 Price Area Acres Rooms Baths £128,500 1220 1.50 6 2 £142,000 1670 0.74 7 2 £146,000 1330 0.25 6 2 £159,000 1560 1.38 8 1 £186,000 1430 0.40 7 1 £174,000 1730 1.95 6 2 £119,000 2210 1.34 8 2 £198,000 1780 0.52 9 1 £134,000 1290 2.30 6 2 £153,000 1340 0.70 7 1 £170,000 1810 1.20 8 1 £185,000 1740 1.90 6 2 £91,000 1330 1.76 6 1 £154,000 2700 0.60 9 3 £125,000 1400 0.55 7 1 £145,000 1850 0.38 7 2 £146,500 1750 0.72 8 2 £118,000 1000 0.40 8 1 £210,000 2950 1.20 9 3 £138,000 1900 0.57 8 1

11 Indicate the possible applications, in marketing research, for:

(a) cluster analysis

(b) factor analysis

(c) conjoint analysis

(d) multidimensional scaling.

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