Normal Distribution of Psychology Data Sets

Posted: August 27th, 2021

Student’s Name

Instructor’s Name

Course

Date

Psy 4-1

Normal Distribution of Psychology Data Sets

Normal or Gaussian distribution refers to a probability distribution, which is symmetric on the mean, implying that the average data has more occurrence than the far away. A normal distribution on a graph gives a bell-like shape. Additionally, the probability bell curve implies that the mean is zero, and the standard deviation is one. Equally, the normal distribution n has zero skew and kurtosis of three. The Gaussian distribution is essential in representing the psychology data sets. Thus, a normal curve is created by a graph representing Gaussian distribution on the histogram since the bell-shaped mean is the same as its mode and median.

Consequently, the normal distribution in the psychology data sets is attractive. It is centered on the mean implying that in a normally distributed population, for any sample size presented by n, the X bar distribution will be normal. Additionally, the confidence intervals for the entire population mean in the proportion is the normal distribution. Equally, according to the central limit theorem, the sampling distribution means is estimated to be equal to entire population mean (mu) ina large sample size (n). Besides, when the original standard deviationof the population is divided by the square root of the sample size (n), it makes the standard deviationequal to standard error of the sample mean. Therefore, the normal distribution has two standard deviation parameters and means and holds the empirical rule. The rule indicates that 68% of the total observations fall within one standard deviation of the population average in a bell-shaped curve and symmetrical distribution. Also, within three standard deviations of the population mean is 99.7% of the whole population. Likewise, within the two standard deviations is 95% of the overall observations. Hence, the distribution is essential in the psychology data sets. It indicates the mean resources costs and uses, and sample means employed in t-test and linearregression techniques like ordinary least squares.