Comparing Memory Test Performance

Because the p-value of .035 is less than the significance level of .05, I will reject the null hypothesis at 5% level.

Testing allows the p-value that represents the probability showing that results are unlikely to occur by chance. A p-value of 5% or lower is statistically significant. The p value helps in minimizing Type I or Type II errors in the dataset that can often occur when the p value is more than the significance level. The p value can help in stopping the positive and negative correlation between the dataset to reject the null hypothesis and to determine if there is statistical significance in the hypothesis. Understanding the p value is very important in helping researchers to determine the significance of the effect of their experiment and variables for other researchers

Note: the program we used on this worksheet said the results were not significant, but then in statistical notion it had “p < 0.05”. That is confusing because I believe it should be “p >

This p-value signifies there is not a significant relationship between the independent variable and the dependent variable. An interesting relevant percentage is 60% of females answering the question responded “disagree” to the statement. Further, in the male column, there seems to be some variation among the responses. There is at least one response in every answer, except for strongly agree were 40% strongly agreed with the statement.

The level of significance was set at .05. The proportion of the people who were treated with the shot vaccine and who developed the flu equaled (=) .16, and the proportion of the people who were treated with the nasal spray vaccine was .24. The calculated p value equaled (=) .0008.The hypothesis for this research study is asking which vaccine was more effective when looking at the outcomes of the subjects who did not fall ill with the flu. The scientific approach isn’t an assumption that one of these results is going to be better than the other one. This is at least true until there is dependable proof to prove otherwise.

Results: The p-value of 0.00203 is p&lt;0.05 thus we reject the null hypothesis and conclude that there is a significant difference between the two means.

Thus, the choice by Richmond, Merrick, Green, Dinh, & Iedema (2011) to report p-values and confidence values (CI) in establishing the significance of the results assists in enhancing the reliability and validity of the study. Whereas, Tobiano, Chaboyer, & Mcmurray (2012) adopted thematic analysis in data analysis, which facilitated flexibility while maintaining research rigor. The straightforward nature of the thematic analysis also contributes in enhancing the validity of the provided evidence. In the case of Sand-Jecklin & Sherman (2014), the presentation of the findings in terms of means, standard deviation (SD), p-values and degree of freedom (df), coupled with the use of tables in presentation facilitated easier understanding of the values and identification of any trend likely to emerge. The presentation was critical in improving the validity of the findings

With the P-value of 0.0033 being less than the alpha at 0.05 we will reject the null

A qualitative question was inquired from the participants asking them to discuss why they like consuming caffeinated beverages as well as to list the types of caffeinated drinks they consume. A very prominent answer was that the reason that they consume caffeinated beverages was that it provided them energy. All but one participant included this in their answer. Many of the participants have also explained that the beverages helped them focus in class. A similar answer among the respondents were “It gives me energy” and “It helps me focus in class” as well as “It helps me stay focused”. One participant, a college graduate, similarly answered “It helps me stay awake during my long commute”. In addition, another predominant reason why the respondents in this sample liked caffeinated beverages was because of the taste. Every participant answered that they either liked the smell and or the taste of coffee. One participant answered “Coffee is always a good idea” while another participant answered “Drinking Monster taste good and makes me feel very good!” Furthermore, when listing the types of drinks the participants consumed, coffee and tea were majority of the replies. Many of them listed the types of coffee they enjoyed such as dark/light roast, Americano, expresso, and a cold brew type of coffee. High school level students and college level students listed either

The study is to see whether expectation of having consumed caffeine can improve performance and mood. It also wants to see whether caffeine effect the expectancy on reward responsivity. In order to conduct the study there was a sample of 88 non-smoking undergraduate, coffee drinkers. They were randomly assigned to caffeine or placebo condition.

The studies were based on small sample sizes, many times just groups of 15 to 20 people and didn’t cover a good length of time, with the average period three to four months. This type of small sample size and short time period might produce quick results for the initial goal of determining if there's increase short-term performance but lack the long-term results of the how the drinks affect the person body and internal organs. More studies about how energy drinks affect short workouts vs. long workouts and the effect energy drinks have on high-intensity interval training vs steady-state cardio workouts would be very helpful. A study that followed participants for a long period of time, possibly for years, and took into account those who consistently used and consumed mass amounts of energy drinks, would be extremely beneficial in understanding who is harmed by its contents and by how much that harm affects their physical capabilities in their later

The statistical significance was documented from the analysis of variance for the scores from the outcome measures. The significance was recognised by the group (.01) as well as when the week and group were in contract (.00) during the treatment and follow-up. The statistics are significant as the values are from 0 at the 0.05 level; it occurs when the values of the confidence interval are on the zero side (Alladin, et al.2007).

Hypothesis - The intake of caffeine through energy drinks will decrease performances in people. the traits of people are not going to change by the intake of caffeine but instead me enhanced. their performances will be impaired due to overstimulation in the brain, which will make it a lot more difficult to interact with others and perform a task. According to a study that was conducted by John hughes, and Anthony Liguori, they found that caffeine can over arouse people and their performance however, supports my prediction.The subjects were tested with a battery of self-report visual analog scales and the Digit Symbol Substitution Test.

The p value is .001, which shows that the data is not normal. However, this test is more reliable with larger sample sizes. Therefore, if there was a larger sample size here, the results of this test may differ from above.

Before the two main hypotheses are tested, a complimentary analysis of the findings may lead to a