The paper "Analytical Approach to Economics and Finance" is a decent example of a Macro & Microeconomics assignment. Mean: The mean is the average and is computed as the sum of all the observed outcomes from the sample divided by the symbol for the by the sample mean. The average of the total 50 observations of the housing prices, the average housing prices will be $ 394483. Standard Error: $ 12805 is the adjusting figures of the sample mean (394483) to achieve the real mean. It shows how much the sample mean was close to the real mean. Median: The median is the middle score.
Melbourne may choose a central or middle placed value of $ 385 for the pricing of houses. Mode: It is the value that occurs most in a distribution. Housing prices can be chosen from the most appearing price of the quarterly median prices. In this case $320 Standard Deviation: It is a measure that is used to quantify the amount of variation of an asset of data. The variability of the prices from the mean is $ 89640 and it shows how much the prices vary from the mean prices. Kurtosis: It shows the sharpness of the peak of the frequency distribution curve.
The kurtosis of 1.34 shows that prices are relatively higher at the peak thus the distribution is not normal. Skewness: It is a measure of the asymmetry probability distribution of a valued random variable around its mean. 0.128 is the skewness which is above the normal distribution of zero the tail on the right side will be longer or fatter. The probability that the House Price would be above $ 700,000 Probability for Therefore, the probability that the house price would be above $ 700,000 is: The probability that a group of 20 houses will have an average house price of $ 500,000 Probability for Therefore, the probability that the house price would be above $ 700,000 is: An outlier is the data value that falls out of the shape of the distribution of a variable.
It is an indicator that a special case is worth investigation. It is a value that lies out of the normal distribution data. The outlier has minimal effect on the median. It is so because there is a lot of data clustered to the median making the effect slight on the median.