Run Test Report Examples

The run test is used to determine if the data set is taken from the random process. It is based on a binomal distribution. For the selected case, the binomial distribution is negative or positive stock return. The test aims to determine of the negative and positive stock returns take place due to random factors.
For the run test, the zero hypothesis H0 states that the negative and positive stock returns appear randomly, the alternate hypothesis H1 states that the negative and positive returns appear not randomly, but dependent on some factors. After this, the test statistics z-value calculates, Z = 0.2.
Thus, the test has been run. The critical value of z-test is -0.84, and Z < |critical z-test|, 0.2 < 0.84.

The negative z-score indicates that that the value is below the mean or shifted left.

The absolute value 0.84 states that the score does not significantly differ from the chanve (random) values.
Since the test statistic is less than the critical value, it can be concluded that the data are random at the 0.05 significance level. Thus, the negative and positive stock returns are random. The stock return is fluctuating, and there are no objective (economical, political, etc.) reasons that cause the value of stock return. On the other side, this means that currently the market is stable.
The value for negative stock return is on the left side of the distribution since N2 < Mean (21 < 29). If the negative and positive stock values are random, they fall within the region of z-values 0.025 0.975 of the z-distribution. The interval which the data for negative and positive stock values fall are indicated by z-value, which is 0.84, so the values are within the region 0.08 0.092, which is within the random distribution region.