3. Descriptions are provided for several types of series: random, stationary, trending, and seasonal. Identify the type of series that each describes.a. The series has basic statistical properties, such as mean and variance, that remain constant over time.b. The successive values of a time series are not related to each other.c. A high relationship exists between each successive value of a series.d. A significant autocorrelation coefficient appears at time lag 4.e. The series contain no growth or decline.f. The autocorrelation coefficients are typically significantly different from zero for the first several time lags and then gradually decrease toward zero as the number of lags increases.
Inverse Normal Distribution
The method used for finding the corresponding z-critical value in a normal distribution using the known probability is said to be an inverse normal distribution. The inverse normal distribution is a continuous probability distribution with a family of two parameters.
Mean, Median, Mode
It is a descriptive summary of a data set. It can be defined by using some of the measures. The central tendencies do not provide information regarding individual data from the dataset. However, they give a summary of the data set. The central tendency or measure of central tendency is a central or typical value for a probability distribution.
Z-Scores
A z-score is a unit of measurement used in statistics to describe the position of a raw score in terms of its distance from the mean, measured with reference to standard deviation from the mean. Z-scores are useful in statistics because they allow comparison between two scores that belong to different normal distributions.
3. Descriptions are provided for several types of series: random, stationary, trending, and seasonal. Identify the type of series that each describes.
a. The series has basic statistical properties, such as
b. The successive values of a time series are not related to each other.
c. A high relationship exists between each successive value of a series.
d. A significant autocorrelation coefficient appears at time lag 4.
e. The series contain no growth or decline.
f. The autocorrelation coefficients are typically significantly different from zero for the first several time lags and then gradually decrease toward zero as the number of lags increases.
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