Title Student Name Institution Affiliation The major difference between null hypothesis and alternative hypothesis is that, the alternative hypothesis is a statement of inequality between variables, in other words it contains an inequality sign between the variables being tested (Hausman, J. A. 1978). In addition alternative hypothesis show that there is an effect or difference between the variables being studied. On the other hand null hypothesis is a statement of equality between sets of given variables and an equal sign is being used between the variables. Null hypothesis is a no effect or a no difference hypothesis. Whereas alternative hypothesis describes the population parameters that the sample data if the predicted relationship prevails, on the other hand null hypothesis describes the same if the predicted relationship does not prevail. Another difference between null hypothesis and alternative hypothesis is that, alternative hypothesis refers to sample while null hypothesis refers to a population and hence alternative hypothesis can be tested directly …show more content…
The coefficient of variation is in a way that 0?r2?1, and it denotes the strength of the linear relationship between the dependent and the independent variable. According to (Rousseeuw, P. J., & Leroy, A. M. 2005)The coefficient of variation is also a measure that allows a person to determine how certain one can be making prediction from a given model or graph .The coefficient of variation represents the percent of the data that is the closest to the line of the best fit in the scatter plot. For example given that r=0.921 , thus r2 =0.85 ,which indicates that 85%,of the total variation in y can be illustrated by the linear association between x and , while the remaining 15 % remains
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.
The following passages contain comparative inferences, also known as argument by analogy. Each analogy is faulty. Read each passage carefully. Your textbook identifies five (5) criteria for evaluating analogies: familiarity, simplicity, comprehensiveness, productivity, and testability. In a paragraph or two identify which characteristic of comparative inferences the passage is failing at. Explain how the passage is not meeting that criteria and suggest a way the passage could be improved. Each passage is worth ten (10) marks.
Mendel wrote that genes are passed from parents to their children and can produce the same physical characteristics as the parents.
α is the intercept of the regression line, and β is the slope of the regression line. e is the random disturbance term. The equation Y = α + βX (ignoring the disturbance term “e”) gives the average relationship between the values of Y and X.
48): A research hypothesis is a researcher’s prediction of the expected results of a study. Research hypotheses can be directional, in which the researcher states the exact “nature of the expected difference or relationship” between factors, or nondirectional, in which the researcher states that there will be some type of relationship between factors, but is not yet sure what that relationship will be. (McMillan, 2012, p. 48)
The test of significance is designed to assess the strength of the data against the null hypothesis. A test of significance assesses this in terms of probability. In this study our null hypothesis or H0 states that the percentage of nuts for all 52g candy bars is equal to the percentage for all 96g candy bars.
Descriptive statistics is a procedure of organizing sample data. This procedure allows readers to be able to understand and describe the data’s importance. Descriptive statistics allows an individual to quickly understand the data and make predict an individual score; however, descriptive statistics does not describe all data in the sample. Inferential statistics is a process that determines whether sample data accurately represented the relationship to the population. In other words, one uses inferential statistics to determine if the sample data is believable.
Although the intended hypothesis was not determined by the researcher in this study, I would determine it to be a null hypothesis as nurse-patient interactions (independent variable) have no effect on diabetes related outcomes (dependent variable). The alternative hypothesis would then reject the null hypothesis by stating that nurse-patient interactions do affect diabetic related outcomes. We use the nurse-patient interaction as the independent va...
Ho 2. Alternative Hypothesis called research hypothesis • Always contain educated test • Study / research that’s why it is called Educated • Alternative
Bachman, R and Schutt, R. (2012) state, “ a hypothesis is an idea or a claim linking or establishing a relationship between two variables.” Specifically, a hypothesis may not be definite or true until proven to be factual by research, experiments and evidence. An independent variable leads a researcher to find meaningful, truthful and extensive observational data that concludes that the independent variable affected or caused a change to the dependent variable.
A question that epistemologist ask is what sort of factors make beliefs justified. That is to say, could there possibly be a set of basic justified beliefs that rationally define all of your other beliefs? Or perhaps there are no foundational beliefs, but rather an infinite amount of beliefs that explain the ones that came before it. Are these beliefs based on evidence or perhaps something more? Epistemology attempts to answer these such questions.
Standard Deviation is a measure about how spreads the numbers are. It describes the dispersion of a data set from its mean. If the dispersion of the data set is higher from the mean value, then the deviation is also higher. It is expressed as the Greek letter Sigma (σ).
The father of quantitative analysis, Rene Descartes, thought that in order to know and understand something, you have to measure it (Kover, 2008). Quantitative research has two main types of sampling used, probabilistic and purposive. Probabilistic sampling is when there is equal chance of anyone within the studied population to be included. Purposive sampling is used when some benchmarks are used to replace the discrepancy among errors. The primary collection of data is from tests or standardized questionnaires, structured interviews, and closed-ended observational protocols. The secondary means for data collection includes official documents. In this study, the data is analyzed to test one or more expressed hypotheses. Descriptive and inferential analyses are the two types of data analysis used and advance from descriptive to inferential. The next step in the process is data interpretation, and the goal is to give meaning to the results in regards to the hypothesis the theory was derived from. Data interpretation techniques used are generalization, theory-driven, and interpretation of theory (Gelo, Braakmann, Benetka, 2008). The discussion should bring together findings and put them into context of the framework, guiding the study (Black, Gray, Airasain, Hector, Hopkins, Nenty, Ouyang, n.d.). The discussion should include an interpretation of the results; descriptions of themes, trends, and relationships; meanings of the results, and the limitations of the study. In the conclusion, one wants to end the study by providing a synopsis and final comments. It should include a summary of findings, recommendations, and future research (Black, Gray, Airasain, Hector, Hopkins, Nenty, Ouyang, n.d.). Deductive reasoning is used in studies...
The research hypothesis is to test what is most effective/safe when college students consume energy drinks and with alcohol. The hypothesis statement describes the expected relationship between the independent and dependent variables in this research. In this case the relationship are positive or negative as one increases or decreases relationship. The hypothesis is not clear, but it should or could be. (Creswell, J. W., 2013).
An Analysis of "On the Other Hand" "On the Other Hand", what is on the other hand? Rachel Hadas tells about the living, the dead and shows the reader the other side of usual thoughts about the dead and living. She lists the faults of the living and the virtues of the dead, in order to explain her first statement, "it is no wonder why we love the dead". Yet, then turns everything around again in the last statement of this free verse poem. Rachel Hadas poem, "On the Other Hand" clearly depicts the many differences of the "brittle, easily wounded" living and the "patient, peaceful" dead.