One-way analysis of variance (one-way ANOVA) is a technique that is used to determine whether there are statistically significant differences between the means of two or more samples (using the F distribution) when there is only one independent variable. In this case, we used a one-way ANOVA to understand whether students' thoughts on those immigration questions differed based on ethnicity (dividing ethnicty into three indepedent groups (Asian, Hispanic and White students). So, we have three categories, Asian, Hispanic, and Asian. So, our X variable is the ethnicity, and its categorical. The outcome is their opinions on immigration questions, which in this case, it's a one to five, where five is strongly agree, one is strongly disagree. So,
our outcome variable or our Y variable is continuous. Our X variable is categorical, Y is continuous, thus we can do a one-way ANOVA. There are some limitations of one-way ANOVA. It is an omnibus test statistic, which cannot tell you what groups were statistically different. The F-test is used to evaluate differences in means. The smaller the difference in variance between groups the smaller the F-value. The smaller the F-value, the less likely the null hypothesis is rejected. In this case, the F-value is relative small, which is 1.08, so that farther concludes that we cannot reject the null hypothesis and we're not affected by its' limitations.
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.
Assistant Principal Howard implies that gender is an issue in relation to the way she is being treated. Do you agree with her? Provide a rationale for your response. I do not agree that gender is the issue in how she was treated. I think that she was named associate principal because of her ability to lead. Mr. Varber considered her to be a valuable asset on his administrative team because of her experience. He also relied on her to manage the school in his absence. She did this effectively. According to the case study it appeared that Mayor Shea and Superintendent French were aware of Mrs. Howard’s managerial and leadership skills, which helped their decision to appoint her as associate principal. This decision would
Strengths for Duquesne University would be that it is nationally ranked number 115. This is a number that can beat many competitors and creates benefits for those that attend. Classes that have fewer than twenty students is 40.9% and classes that have fifty or more students is only at 9%.. (http://colleges.usnews.rankingsandreviews.com/best-colleges/duquesne-university-3258/rankings). Duquesne is located in Pittsburgh Pennsylvania and is known to be one of the top places to live in the country. Pittsburgh is considered the most livable and resilient. There is a young crowd that could be an interest for young adults, also this city is considered to be the third safest cities in the states (https://fitt.co/pittsburgh/pittsburgh-best-city/). Religious values are what many people look for to keep that connect they have with their beliefs, having these values instilled in the curriculum could be a benefit view for parents and students.
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.
A sample of children ranging from 4 to 13 years old are going to be asked to watch a Rainbow Brite video. The children will be randomly picked from a childcare center. To ensure that the children are going to be randomly assigned, the children will range in different age groups. The first group will consist of 4, 6, and 8 year olds. The second group will consist of 10,12, and 14 year olds. It would have to be a field experiment because you have to go out and collect the data.
In order to conduct a Chi-Square test of Independence, there must be either two categorical or ordinal variables (Mirabella, 2011). In this case, to determine if there is a difference in majors chosen by men and women the test of Independence will be used because of the two categories which are male and female. Similar to the Goodness of Fit test, the Chi-Square test of Independence possesses the two variables for gender (Mirabella, 2011). Therefore, it is not uncommon that research involves the Chi-Square Independent test when determining various important differences between variables.
In this analysis the null hypothesis is that the variable are independent, in other words whether or not a person has gotten their flu shot is unrelated to which group they are in. The Alternate hypothesis is that whether or not a person has gotten their flu shot is related to which group they were placed in, the variables are not independent. The results of this analysis are that the chi-square value is 4.1620049, which is nonsignificant according to the table on page 416 of the text which shows that the level of significance for 2 degrees of freedom is 5.99. The p value of 0.1248 is also indicative of a nonsignificant result. Based on the results of this analysis and the resulting significance the keep the null hypothesis.
...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.
In order to test this hypothesis 60 students will be randomly recruited. In order to get my 60 participants, I will pick students who id begins with the numbers 08. A total of 30 females and 30 males will be chosen, all psychology undergraduate students from Texas A&M International University, largely in the age range 20-25 years. No payment, other than receive 5 points of extra credit, will be offered for participation.
of 50 students (25 girls, 25 boys) from year 7. I have data from a
The study consisted of 3200 participants (all men) .They all were given questionnaires and from their responses and their manner, each participant was put into one of two groups:
The study design I’ve created consists of data from watching two news networks. My first step was watching the two news stations, Fox News and MSNBC. The reason why I chose these two news channels was because they represent different political parties. Fox News is known to be conservative, and MSNBC is known to be liberal. Since they have different ideologies, their rhetoric upon issues representing minorities would represent their political party.
On the other hand, Quantitative research refers to “variance theory” where quantity describes the research in terms of statistical relationships between different variables (Maxwell, 2013). Quantitative research answers the questions “how much” or “how many?” Quantitative research is an objective, deductive process and is used to quantify attitudes, opinions, behaviors, and other defined variables with generalized results from a larger sample population. Much more structured than qualitative research, quantitative data collection methods include various forms of surveys, personal interviews and telephone interviews, polls, and systematic observations. Methods can be considered “cookie cutter” with a predetermined starting point and a fixed sequence of
Analysis of variance (ANOVA) is a collection of statistical models used in order to analyze the differences between group means and their associated procedures. In the ANOVA setting, the observed variance in a particular variable is partitioned into components attributable to different sources of variation. The following equation is the Fundamental Analysis-of-Variance Identity for a regression model.
Whether or not people notice the importance of statistics, people is using them in their everyday life. Statistics have been more and more important for different cohorts of people from a farmer to an academician and a politician. For example, Cambodian famers produce an average of three tons or rice per hectare, about eighty per cent of Cambodian population is a farmer, at least two million people support party A, and so on. According to the University of Melbourne, statistics are about to make conclusive estimates about the present or to predict the future (The University of Melbourne, 2009). Because of their significance, statistics are used for different purposes. Statistics are not always trustable, yet they depend on their reliable factors such as sample, data collection methods and sources of data. This essay will discuss how people can use statistics to present facts or to delude others. Then, it will discuss some of the criteria for a reliable statistic interpretation.