In this case study, we can use the data provided to analyse the number of cups of coffee consumed in a week for the males and females, by using SPSS. It is clear that it can be used the independent-samples t-test for this question. For this case, we can use the independent-samples t-test to compare the mean scores on some continuous variable for two different groups. In other words, we need one independent variable (e.g. males and females) and dependent variable (e.g. the number of cups of coffee consumed a week) to test significant difference in the mean scores for the two groups. From the coffee drinking habits research, we could obtain this statistic of how males and females differ significantly in terms of their coffee consumption during …show more content…
As a result, we have to report the t-value by selecting the second line of the table. (d) In this case study, the Mann-Whitney U Test could be used to address this question. Using for independent samples, the non-parametric alternative to the t-test is the Mann-Whitney U Test. Rather than using the t-test to compare means of the two groups (males and females), we can compare medians by using the Mann-Whitney U Test. The Mann-Whitney U Test can be used for differences between two independent groups (males and females) on a continuous measure (the number of coffee consumption a week). Using this method, one can convert the scores on coffee consumption to ranks across the two groups (males and females). There are several key points that can be addressed here. For example, we are considering how males and females differ in their consumption habits of coffee on a weekly basis. Another point is do females have higher consumption of coffee habits a week than males? Therefore, we can evaluate whether the ranks for the two groups (males and females) are a statistically significant difference or not. (a) In this case, it is important to know that the two-way ANOVA method can be addressed in this
Null hypothesis: The author’s spouse cannot tell the difference between Keurig brewed Emeril’s Big Easy Bold coffee and any other brand coffee brewed in the same manner.
For this statistical inference, the question was whether the means were truly different or could they have been samples from the same population. To do draw a conclusion, we must first assume normal distribution. We must also set the null hypothesis to m1 - m2 = 0. And per this assignment we must set the a-level at .05 and the hypothesis alternative to m1 - m2 ¹ 0; thus requiring a two-tailed test.
Michele Obama once stated, “If my future were determined just by my performance on a standardized test, I wouldn 't be here. I guarantee you that.” The First Lady is, in other words, to say that standardized testing was a major factor into her life’s outcome and her scores could have potentially not put her in her position of power that she is highly recognized in today’s society. Although standardized tests do play a large role in any college application, standardized testing may not count as much toward one’s college admissions or success because standardized tests are not the only factor toward college applications, these tests only benefit a specific target group of people, and standardized tests are better used for giving insight on one’s
Thi cunclasoun frum thi stetostocel tist sappurts thi fondongs uf thi hyputhisos. Wrotir huwivir duis nut nicisseroly egrii whulihiertidly woth thi risierch ertocli. Wrotir fiils thiy eri sumi lomotetouns tu thi stady, ot duis nut eccuant fur uthir fecturs on thi eduliscints lofi, bisodis thior chusi on masoc thet mey lied tu saocodel thuaghts end fiilongs.
A scholarly journal written by an anonymous author sheds light on the importance of standardized testing by showing its efficiency in higher level education. This article provides a solid counterargument for the use of standardized tests which is standardized tests being a good source of predicting grades throughout college as well as whether students will stay long enough to graduate. It is also able to establish that the SAT is effective in forecasting a grade-point average through the fourth year as well as predicting students study habits. The
Tarnopolsky, Mark. (1999) Gender Differences in Metabolism: Practical and nutritional implications; Caffeine. Boca Raton: CRC Press, 155-200
For this study ten participants were chosen to complete the study. For this particular study, the participants had to be the eldest and youngest child from the same family. They both also had to be raised in the same household. The pairs were picked at random and then asked to complete the test. There were three males tested and seven females tested.
The third question received only forty responses due to the fact that it didn’t relate to the ten respondents of the survey that claimed to not drink any soda at all. This question asked my classmates whether they drink caffeinated or non-caffeinated soda. Approximately 93% of respondents drink caffeinated while a small percentage of 7.5% consume non-caffeinated. Results to the third question are listed below in Figure
Standardized testing is obviously trash! Especially if you are a student or teacher who is forced to sit there for four hours! What makes this worse is the fact that you can not talk, draw, or do anything productive. So are these mandatory silence hours even helpful to the education of children or are we just wasting our time.
Collected data were subjected to analysis of variance using the SAS (9.1, SAS institute, 2004) statistical software package. Statistical assessments of differences between mean values were performed by the LSD test at P = 0.05.
Also, the title of the article states the research is a “population study” which is a focus of a quantitative research and a component of a quantitative method. Furthermore, the authors specified a clear defined research purpose which often requires statistical methods to test the hypotheses as well as to look for the cause and effects of the variables so that predictions can be
...ne’s level of interest. The independent variables are the three different groups that are being studied. The ratings given by the participants will represent the dependent variables. The alpha is set as 0.05. According to SPSS, the results show that this study has a significance level of 0.000, which is less than 0.05. Because of this difference, it is appropriate to accept the research hypothesis and to reject the null hypothesis.
Many factors can influence the results of testing this hypothesis. All variables have been controlled except for the variable gender. Both the male and female subjects are close in age (< two years difference), both are nonsmokers, both possess small body builds for their respective gender, and both have no debilitating medical conditions (e.g., asthma, diabetes, heart condition). Controlling these factors allowed for the testing of the hypothesis, which is focused strictly on gender.
In an analysis of the results of four different personality tests, I discovered not only my personality type, but also my study skills and time management skills. I learned that my personality type corresponds with the traits necessary to my desired career in social work. This analysis is helpful in understanding my personality and its relation to my success in college and in life.
The test is administered in similar conditions and similar timing. And the scores of both the groups are analysed for typical statistical parameters such as means and standard deviations.