Descriptive Statistics: The Store Space

A commercial property developer is looking at building a new shopping centre in Johannesburg. He hired a research firm to help him identify whether it will be profitable for him. They began by analysing the store space available in 20 shopping centres in Johannesburg. The following data summarises the results recorded: 115; 210; 108; 203; 116; 174; 164; 145; 129; 135; 121; 135; 175; 198; 161; 111; 108; 165; 178; 201
Question 1: Construct a relative frequency distribution table that summarises the results recorded. Use intervals of 25 𝑚² (e.g. 100.5 –< 125.5; 125.5 -< 150.5...)
Intervals (Classes) Absolute Frequency (Number) Relative Frequency (%)
100.5 -< 125.5 6 30%
125.5 -< 150.5 4 20%
150.5 -< 175.5 5 25%
175.5 -< 200.5 2 10%
200.5 -< 225.5 3 15%
Total 20 100%

Table: Frequency distribution of shopping space available in Johannesburg:

Question 2: Construct a histogram with appropriate headings of the numerical frequency distribution.
HIstogram 01 IMM GS Assignment
Question 3: Interpret the results and make a suggestion to the property developer if the average shopping centre in the Johannesburg area is 10 000 𝑚².

It shows that most shopping centres have between 100.5 and 125.5 𝑚² of store space available. Considering the total of 10 000 𝑚², this is a relatively small amount. It is recommended that the property developer proceed with the development of the new shopping center, as the majority of existing centres are already occupied by tenants and have limited available store space. This also indicates a demand among store owners for additional rental space.

Question 4: What percentage of shopping centres has more than 150 𝑚² of space available?

More than 150 𝑚² available:

$$
\frac{5 + 2 + 3}{10} \times 100 = \frac{10}{20} \times 100 = 0.5 \times 100 = 50\%
$$

Question 5: Calculate the coefficient of variation of the available shopping centre space if the variance is given at 1 154.55 𝑚². What does this tell you?

Standard deviation:

$$
\sigma = \sqrt{S^2} = \sqrt{1154.55} \approx 33.98 \, \text{m²}
$$

For the purpose of electronic examinations, the equation can be expressed as follows:

Sigma = sqrt(S^2) = sqrt(1154.55) = 33.98


Coefficient of Variation:

$$
CV = \frac{\sigma}{\bar{x}} \times 100 = \frac{33.98}{150} \times 100 \approx 22.65\%
$$

For the purpose of electronic examinations, the equation can be expressed as follows:

CV = (Sigma / Mean) * 100 = (33.98 / 150) * 100 = 33.98


Interpretation:

The Coefficient of Variation (CV) provides a measure of the relative variability of a dataset by comparing the standard deviation to the mean. A CV of 22.65% in this case suggests that there is moderate variation in the availability of shopping centre space. This could imply that there are some periods of high availability, but overall, the space fluctuates considerably around the mean.

Standard Deviation (σ = 33.98 m²):
The standard deviation represents the absolute variability or spread of the available shopping centre space data. It tells you that, on average, the available space deviates by 33.98 m² from the mean value (150 m²).

Coefficient of Variation (CV = 22.65%):
The CV is the relative variability. It tells you how large the standard deviation is compared to the mean, expressed as a percentage. In this case, it indicates that the standard deviation is 22.65% of the mean.

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