Normal Distribution and Points

Hypothesis is typically used in quantitative research only. Moreover, when a question poses an inquiry on the relationship between two variables, a hypothesis is a statement declarative in nature of the relationship between different variables (Pajares 2007). A researcher chooses whether to use a question or a hypothesis depending on the purpose of the research, its objectives, the methodology for the research and the preference of the audience to receive the research. A researcher must be able to interpret the final outcome with reference to the research questions or the hypothesis used (Pajares 2007). A research requires a minimum of two hypotheses namely a null and an alternative hypothesis.

Research results tell us information about data that has been collected. Within the data results, the author states the results are statistically significant, meaning that there is a relationship within either a positive and negative correlation. The M (Mean) of the data tells the average value of the results. The (SD) Standard Deviation is the variability of a set of data around the mean value in a distribution (Rosnow & Rosenthal, 2013).

Standard Deviation for the mean column is 0.476Standard Deviation for the median column is 0.754Standard deviation for the mean column has least variability

The goal of inferential statistics is to end up rejecting the null hypothesis and concluding that a significant relationship exists; therefore, the null hypothesis always presume no relationship.

Their scores are: 55, 47, 62, 27, 50, 49, 66, 53, 50, 44, 63, 59.

* Statistical significance of the coefficient – This is a statistical test that confirms if the coefficient regardless of its value is robust and different from zero. Also referred to as the P-value.

In an experimental research, the use of a research question answers the thesis statement that enables one to research about a problem (Yin, 2013). From the experiment, the research question can be clearly stated as “which vaccine is more effective for preventing getting the flu”. In this case, the problem being researched about is the flu the possible solutions to this problem which the use of vaccines is being analyzed. The null hypothesis of this experiment states that there is no effective vaccine for preventing getting the flu while the alternative hypothesis states that there is an effective vaccine for preventing getting the flu.

3) This is also a correlation approach because there is no actual manipulation of the variables.

8. Analyze: How does the standard deviation relate to the consistency and range of a data set?

There is a null hypothesis and an alternative hypothesis. The null hypothesis usually states there is no difference and an alternative hypothesis states there is. A result is positive if it rejects the null hypothesis. A result is negative if it does not reject the null

c) What is the null and alternative hypothesis? Do the data results lead you to reject or fail to reject the null hypothesis?

The mode is the most frequent score in our data set. On a histogram it represents the highest bar in a bar chart or histogram. You can, therefore, sometimes consider the mode as being the most popular option

"There are several different kinds of relationships between variables. Before drawing a conclusion, you should first understand how one variable changes with the other. This means you need to establish how the variables are related - is the relationship linear or quadratic or inverse or logarithmic or something else" ("Relationship Between Variables ", n.d)

Statistical dispersion is measured by a number system. The measure would be zero, if all the data were the same. As the data varies, the measurement number increases. There are two purposes to organizing this data. The first is to show how different units seem similar, by choosing the proper statistic, or measurement. This is called central tendency. The second is to choose another statistic that shows how they differ. This is known as statistical variability. The most commonly used statistics are the mean (average), median (middle or half), and mode (most frequent data). After the data is collected, classified, summarized, and presented, then it is possible to move on to inferential statistics if there is enough data to draw a conclusion.

Statistical quality control can be divided into three broad categories: 1. Descriptive statistics are used to describe quality characteristics and relationships. Included are statistics such as the mean, standard deviation, the range, and a measure of the distribution of data.