We have been analyzing quatitative data over the past few weeks using descriptive statistics. Please share how you analysed your pre-test and post-test data using descriptive statistics.
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Bethlehem Moravian College 
In order to analyzing quantitative data the most suitable way is to construct a table which shows the sores obtained in the pre-test and the post test done by the participants. This can be done using the Microsoft excel software. This table has four columns namely: participants name, pre test scores, post test scores and difference of scores in percentage. The pre test and post test scores obtained by each participant should be posted respectively in the table. In order to find the difference of scores for each participant the researcher should subtract the score obtained in the pre test from the one obtained in the post test. The SPSS software can show whether or not the differences between the sores are significant.
When that has been completed the next step is to find the mean of the pre-test and the post test sores. In excel this can be done by selecting the auto sum icon and choosing average or in the function bar you type:=AVERAGE(the column where the score start: the column where the score end). After which you calculate the standard deviation. The Standard Deviation is a measure of how spread out the sores obtained by the participants are. When calculating the standard deviation using excel you type in: STDEV(B2:B10) in the function bar. In order to find the standard deviation without the excel you find the square root for the sum of each score subtracted by the mean score which is all squared then this is divided by the total number of scores. This information can be used to construct a comparative line graph or a bar chart.
The standard deviation and the mean can be used to tell how well the student did or how poorly. This is a result of how widespread the standard deviation is around the means or how tightly packed the standard deviation is around the means.
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The descriptive statistics of the quantitative research data is measurable as data can be attained by the mean scores of the participants of both the pre-test and post-test`. A table with four columns is used to represent the participants, pre-test, post-test and the difference in scores of each participant. To calculate the mean scores of all participants, it is all the scores of the pre-test and post-test added and then divided the result by the number of scores. To get the difference of both pre-test and post-test we subtract the pre-test from the post-test to get the difference. To calculate the standard deviation of mean scores it is the square root of the sum of each score minus the mean score all squared divided by the number of scores. With the standard deviation it shows the gap between scores, that is how wide spread or how close the students’ scores are. After all scores have been calculated the results can be shown on a comparative bar chart or a comparative line graph which of course, will compare each score but the (SPSS) is used to tell how scores are measured and can tell whether or not the each score is significant. In other words descriptive statistics helps to better manage large amount of data by condensing the data into quantifiable or measurable proportions. This makes it easier to group data without altering or changing the data.
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