hypotnesis tCstng 1OF Both one-tailed test and two-tailed tests. A teacher wants to find out if the webcasting methods of teaching social sciences subjects is more effective than the existing standard method of teaching. Two classes of igiicantly different rea of the manager? Use a = 5%. Perform the nproximately equal intelligence were selected. From one class, the teacher randomly selected a group of students as experimental group for webcasting methods. From another class, the teacher then selected another group of students as sample for existing standard method of teaching. After one trimester, the same tests were given to the students. Their mean scores are shown in the following table: Method of teaching Mean score Standard deviation Sample size Webcasting method x, = 82.3 S = 12 N = 42 %3D Existing standard method X, = 78.5 S, = 9 ng = 38 %3D Test the hypothesis whether or not the webcasting method of teaching social sciences abjects is more effective than the existing standard method of teaching. Use a = 0.05. -1 TEST OF HYPOTHESIS USING THE Z-TEST
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.
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