T-Test Statistics

In: Business and Management

Submitted By weps683
Words 1270
Pages 6
RESEARCH ARTICLE
Source: LoGalbo, A., Sawrie, S., Roth, D. L., Kuzniecky, R., Knowlton, R., Faught, E., & Martin, R. (2005). Verbal memory outcome in patients with normal preoperative verbal memory and left mesial temporal sclerosis. Epilepsy and Behavior, 6 (3), 337–41.
Introduction
LoGalbo et al. (2005) conducted a study to examine the “risk of verbal memory loss in patients with known structural abnormality (i.e., left mesial temporal sclerosis by MRI) and normal preoperative verbal memory performance who undergo left ATL [anterior temporal lobectomy]” (LoGalbo et al., 2005, p. 337). The researchers found that the “patients exhibiting normal presurgical verbal memory are at risk for verbal memory declines following ATL. These results suggest that functional integrity of the left mesial temporal lobe may play an important role in the verbal memory outcome in this patient group” (LoGalbo et al., 2005, p. 337). However, the researchers do recognize the limitations of their study and note that the small sample size restricts the generalization of the study findings.
Relevant Study Results
“Seventeen patients with left temporal epilepsy, MRI-based exclusive left MTS [mesial temporal sclerosis], and normal preoperative verbal memory were identified” (LoGalbo et al., 2005, p. 337). MTS is a structural abnormality in the brain. “The patients selected for the study were considered to have ‘normal’ preoperative verbal memory, defined as having preoperative performance across the learning (Acquisition) and long delayed free recall (Retrieval) portions of the California Verbal Learning Test (CVLT) of at least a T score above 40 (> 16%ile). The CVLT Acquisition score is the total number of words recalled across the five learning trials. The CVLT Retrieval score is defined as total number of words freely recalled after a 20-min delay. Both of these variables have been…...

Similar Documents

T-Test

...attempt to match eachother on any variable. 2. t = –3.15 describes the difference between women and men for what variable in this study? Is this value significant? Provide a rationale for your answer. t=-3.15 describes the differences between women and men for the mental health variable. It has the smallest p value, at p-0.002 and that is considered significant because the p=0.002 is smaller than alpha that was set at 0.05 for this study. Small p values indicate significant findings. 3. Is t = –1.99 significant? Provide a rationale for your answer. Discuss the meaning of this result in this study. T=-1.99 describes the difference in health functioning between men and women after an MI. t=-1.99 is significant because it’s p value (0.049), is still smaller than alpha that was set at 0.05 for this study. The meaning of this result in this study is that the quality of life measures in regards to health functioning show a significant result. This finding indicates that women had a mean of 17.9 with an sd of 4.1, and men had a mean of 19.3, with an sd of 4.6. Results support the study and findings that, “women rate lower levels in physical and psychological dimensions of quality of life” 4. Examine the t ratios in Table VI. Which t ratio indicates the largest difference between the males and females post MI in this study? Is this t ratio significant? Provide a rationale for your answer. 5. Consider t = –2.50 and t = –2.54. Which t ratio has the smaller p value?......

Words: 363 - Pages: 2

Statistics - Elements of a Test Hypothesis

...Elements of a Test of Hypothesis 1. Null Hypothesis (H0 ) - A statement about the values of population parameters which we accept until proven false. 2. Alternative or Research Hypothesis (Ha )- A statement that contradicts the null hypothesis. It represents researcher’s claim about the population parameters. This will be accepted only when data provides sufficient evidence to establish its truth. 3. Test Statistic - A sample statistic (often a formula) that is used to decide whether to reject H0 . 4. Rejection Region- It consists of all values of the test statistic for which H0 is rejected. This rejection region is selected in such a way that the probability of rejecting true H0 is equal to α (a small number usually 0.05). The value of α is referred to as the level of significance of the test. 5. Assumptions - Statements about the population(s) being sampled. 6. Calculation of the test statistic and conclusion- Reject H0 if the calculated value of the test statistic falls in the rejection region. Otherwise, do not reject H0 . 7. P-value or significance probability is defined as proportion of samples that would be unfavourable to H0 (assuming H0 is true) if the observed sample is considered unfavourable to H0 . If the p-value is smaller than α, then reject H0 . Remark: 1. If you fix α = 0.05 for your test, then you are allowed to reject true null hypothesis 5% of the time in repeated application of your test rule. 2. If the p-value of a test is 0.20 (say) and you reject H0 then,......

Words: 1699 - Pages: 7

Analyzing and Improving Test Using Statistics

...Analyzing and Improving a Test Using Statistics Maurice Isaiah McCall  Introduction: Hypothetical Psychology Test This hypothetical psychology test consisted of five test questions. These test items and questions were not unambiguous and there were no evidence of instructions or explanations given for either test question. In our text it was mentioned there were several steps the admitter need to take before administering, analyzing and improving a test or assessment. There was no evidence these test questions were constructed and that it matched any objective. However the guidelines for packaging the test states [items need to be in a similar format, grouped together, test items need to be arranged from easy to hardest, have items properly spaced as well as checking for directions, clarity and proofreading the test before it is reproduced and distributed]. (Kubiszyn & Borich, p. 223 & 224).  It is very obvious these test questions lack validity and were poorly written, these test questions were more in line with the intended audience partaking in a survey. A survey question refers to the quantitative research or a statistical survey, for the sole purpose of collecting quantitative information about the general population or a product. Each of these test questions contained its own set of problems and uniqueness about them. For example every given answer had an asterisk mark beside of it and for any test taker this is a distraction, and the test itself was......

Words: 1678 - Pages: 7

Analyzing and Improving a Test Using Statistics

...these assessment approaches to validate the effectiveness of the curriculum being used for any subject being taught in the classroom. It can help teachers identify the students that need extra attention in certain areas, and help change the lesson around for a better understanding. Teachers need to make sure if the lessons being taught in the classroom are not just being remembered temporarily, they want to make sure it stays in the student throughout their education; using both assessments can help find out if students are remembering the lessons. Using summative and formative assessment can help teachers create an effective instructional plan to help diverse students, not familiar with our schools curriculum. References: Kubiszyn, T., Borich, G. (2013) Educational Testing and Measurement: Classroom Application and Practive (10th ed.). John Wiley & Sons, Inc., Hoboken, NJ....

Words: 585 - Pages: 3

Statistics Test

...Name: ______________________ BUAD 820 MID-TERM EXAM I There are a total of 5 questions. Question 1 is mandatory. Answer any, but only 3 of the remaining 4 questions. Question 1 (has 5 parts) 1 Consider the data shown in the scatter plot below. Which of the following statements is true about the correlation between X and Y. a) X and Y are mildly, positively correlated b) X and Y are perfectly, positively correlated c) X and Y are mildly, negatively correlated d) X and Y are perfectly, negatively correlated e) X and Y are not correlated OR From the information given, we cannot tell whether X and Y are correlated 2 Five students from the 2000 MBA class took jobs in rocket science after graduation. Four of these students reported their starting salaries: $95,000, $106,000, $106,000, $118,000. The fifth student did not report a starting salary. Can we determine the median salary for all five students in this case (Yes/No)? Justify your answer. If you answer yes, indicate the median value. 3 Seven students from 1998 MBA class took jobs in dot-com companies after graduation. Five of the seven students reported starting salaries of $55,000, $90,250, $90,250, $95,500 and $105,000. Based on this information, is it possible to determine the largest possible value for the median salary for all seven students (Yes/No – justify your choice)? If you answer yes, indicate the largest possible median value. 4 One...

Words: 1108 - Pages: 5

T-Test

...T-test: Salaries of Female and Male Human Resource Managers Christy Newman Argosy University T-test: Salaries of Female and Male Human Resource Managers An independent-samples t-test using the raw measurement data presented was completed to check the difference, if any, of the salaries between female and male human resource managers, t(18) = -0.408, p = 0.688, but no significant difference was found (Female Mean = 62.2; Male Mean = 63.7). The preparation for a statistical analysis test began with a well-developed, clear research question: What is the difference, if any, between the salaries of female and male HR Directors? Next, the null and alternative hypotheses must be defined. The null H₀ is that the salaries of female human resource managers = salaries of male human resource managers. The alternative Ha is that salaries of female human resource managers ≠ salaries of male human resource managers. The next step in the process is to determine the appropriate statistical test and sampling distribution. Since σ is unknown and the number of salaries being tested is less than 100, the t-test will be used. Because we are comparing data from two different groups, the two-sample t-test will be used. We do not know if the variance is different or equal, so we will use the two-tailed t-test for two-sample assuming unequal variances. Subsequently, we have to choose the Type 1 Error rate. For this t-test, α = 0.05, which is the standard rate used by statisticians for......

Words: 804 - Pages: 4

T-Test and Anova

...BUS 310 Notes regarding Two-Sample t-Tests and ANOVAs In Chapter 9, we learned how to conduct a t test of a hypothesis when we were testing the mean of a single sample group against some pre-determined value (i.e., the 21.6 gallons of milk consumption as the national average). This week, in Chapter 10, we will see how to test hypotheses that involve more than one sample group—such as testing to see if males are significantly taller than females. If we have two groups, then the technique that we will use will still be a t test. If we have more than two groups, then we will have to use a different test called Analysis of Variance (ANOVA, for short). The good news is that the decision rules for hypothesis testing that we learned last week are still exactly the same: Set #1: If the absolute value (ignore any negative sign) of the test statistic is greater than or equal to the critical value, then you reject the null. If the absolute value of the test statistic is less than the critical value, you do not reject the null. Set #2: If the p value is less than or equal to α, reject the null. If the p value is greater than α, do not reject the null. (Remember that we must either reject or not reject the null—we never accept the null.) In order to conduct these tests, we will need to use the data analysis feature of Excel, which probably is not installed for you, but that’s OK, because it’s available and pretty simple to install—just follow these steps: ...

Words: 2114 - Pages: 9

Statistics

...Question catalogue: Statistics Self-Study Module Master's programme Media and Communication Science If you are master student of the master programme “Media and Communication Science” and have to fulfill the additional requirement: Self-Study Module Statistics, you have to answer these list of 42 questions. Please answer the following questions concerning statistical methods in social science briefly. Helpful information concerning the questions can be found in the Reader: “Statistics”. Enjoy yourself while answering the questions. Chapter 1 1. A client rates her satisfaction with her vocational counselor on a 4-point scale from 1 = not at all satisfied to 4 = very satisfied. What is the (a) variable, (b) possible values, and (c) score? 2. Give the level of measurement for each of the following variables: (a) ethnic group to which a person belongs, (b) number of times an animal makes a wrong turn in a maze, and (c) position one finishes in a race. 3. Fifty students were asked how many hours they had studied this weekend. Here are their answers: 11, 2, 0, 13, 5, 7, 1, 8, 12, 11, 7, 8, 9, 10, 7, 4, 6, 10, 4, 7, 8, 6, 7, 10, 7, 3, 11, 18, 2, 9, 7, 3, 8, 7, 3, 13, 9, 8, 7, 7, 10, 4, 15, 3, 5, 6, 9, 7, 10, 6 Make (a) a frequency table and (b) a frequency polygon. (c) Make a grouped frequency table using intervals of 0-5, 6-10, 11-15, 16-20. Based on the grouped frequency table, (d) make a histogram and (e) describe the general shape of the distribution. 4. Below are the number......

Words: 3576 - Pages: 15

Two Sample T-Test Essay

...both DBs and WRs each is n = 48. The mean height or arithmetic average for the DBs is 71.6 inches and 74.3 inches for WRs. The standard deviation, how far away the typical observation is from the mean, for DBs is 1.60 and 2.69 for WRs. The 5-number summary for DBs is 69, 70, 71, 73, and 76. For WRs it is 68, 72, 74, 76, and 80. The five-number summary gives information about the location (from the median), spread (from the quartiles) and range (from the sample minimum and maximum) of the observations (Wikipedia 2014). The chart below shows the columns computed for a 5-number summary, Mean, and Standard Deviation. To begin this experiment, I will first check that the conditions for this experiment are valid and then use a two-sample t-test to compare the difference of means of the populations with a .05 level of significance and 95% confidence interval. The first condition is met because the samples are random and the observations are independent. Meaning the knowledge of the DBs height tells nothing about the WRs height. The heights entered are random because the heights were not specifically chosen. The population was chosen by player names (starters) not height. The second condition is met because the populations, like the observations, are independent of each other. The value of DBs tells nothing about the value of the WRs. Condition three is met because the populations are both normal and both population sizes are 25 or more. I expected the population......

Words: 959 - Pages: 4

Statistics

...1. Introduction Poverty, which is measured by the household income lower than poverty line has been identified as the dependent variable in this project. It is important to know which elements are associated with poverty. The purpose of this paper is to evaluate the key determinants of American household poverty in 1980. The four possible determinants will be analyzed in this project, the average numbers of every family (FAMSIZE), URB is the percent of people live in urban, UR is the level of people have no job over 16 years and the median family income in US dollars (INCOME). Descriptive statistics, correlation and regression will be used in this project. 2. Descriptive statistics Variable | Mean | Median | Mode | VAR | STDEV | URB | 58.76034483 | 66.15 | 0 | 1012.828049 | 31.82495953 | FAMSIZE | 3.140172414 | 3.135 | 2.93 | 0.033377163 | 0.182694178 | UR | 9.293103448 | 8.95 | 5.8 | 10.92696915 | 3.30559664 | INCOME | 19240.43103 | 18512 | N/A | 10889936.04 | 329.990309 | POV | 9.120689655 | 9.05 | 8.8 | 6.230792498 | 2.496155544 | 3. Correlation Correlation and regression are techniques for investigating the statistical relationship between two, or more, variables (Barrow, 2013, pp. 238). * Correlation defines the degree to which there is a linear relationship between pairs of variables. Firstly, it is useful to graph the variables to see if anything useful is revealed. In this case, XY graphs are the most suitable and they are shown in......

Words: 1666 - Pages: 7

Statistics

...Additional Problem In order to explain the US defense budget, you are using the data from 1962 to 1981 with the following variables (all measured in billions USD) and estimate the corresponding model (Model 1):(Use α=0.05 for references) Yt: Defense budget outlay for year t X2t: GNP for year t X3t: US military sales in year t X4t: Aerospace industry sales in year t D1t: Dummy variable presenting the military conflict involving more than 100,000 troops; D1t=1 if more than 100,000 troops are involved and equal to 0 if fewer than 100,000 troops are involved. |Dependent Variable: Y Sample: 1962 1981 | |Method: Least Squares Included observations: 20 | |Variable |Coefficient |Std. Error |t-Statistic |Prob. | |C |21.40251 |1.496947 |14.29744 |0.0000 | |D1 |-48.21987 |6.871544 |-7.017328 |0.0000 | |X2 |0.013879 |0.003207 |4.328062 |0.0008 | |X3 |0.073146 |0.203805 |0.358902 |0.7254 | |X4 |1.389753 |0.130197 |10.67423 |0.0000 | |X4*D1 |1.540792 |0.325005 |4.740818 ...

Words: 636 - Pages: 3

Statistics

... Introductory STATISTICS 9TH EDITION This page intentionally left blank Introductory STATISTICS 9TH EDITION Neil A. Weiss, Ph.D. School of Mathematical and Statistical Sciences Arizona State University Biographies by Carol A. Weiss Addison-Wesley Boston Columbus Indianapolis New York San Francisco Upper Saddle River Amsterdam Cape Town Dubai London Madrid Milan Munich Paris Montreal Toronto Delhi Mexico City Sao Paulo Sydney Hong Kong Seoul Singapore Taipei Tokyo On the cover: Hummingbirds are known for their speed, agility, and beauty. They range in size from the smallest birds on earth to several quite large species—in length from 2 to 8.5 inches and in weight from 0.06 to 0.7 ounce. Hummingbirds flap their wings from 12 to 90 times per second (depending on the species) and are the only birds able to fly backwards. Normal flight speed for hummingbirds is 25 to 30 mph, but they can dive at speeds of around 60 mph. Cover photograph: Hummingbird, Editor in Chief: Deirdre Lynch Acquisitions Editor: Marianne Stepanian Senior Content Editor: Joanne Dill Associate Content Editors: Leah Goldberg, Dana Jones Bettez Senior Managing Editor: Karen Wernholm Associate Managing Editor: Tamela Ambush Senior Production Project Manager: Sheila Spinney Senior Designer: Barbara T. Atkinson Digital Assets Manager: Marianne Groth Senior Media Producer: Christine Stavrou Software Development: Edward Chappell, Marty Wright C iDesign/Shutterstock Marketing Manager: Alex Gay Marketing......

Words: 377092 - Pages: 1509

Statistics

...Data. Test for Normal Distribution To proceed with the analysis it is necessary to determine if the data are distributed normally. The Histogram below as well as the Descriptive Statistics (Appendix 1, Table 1b) show that the data distribution is leptokurtic (kurtosis is 2,021) and negatively skewed (skewness -,240). We can determine several outliers (Appendix 1, Table 1c, Table 1d) with extreme ratios. In cases #46 and #178 JSL is more than the highest option provided in the questionnaire. That could be a mistake in data entering or the respondent wanted to emphasise his/her satisfaction level. These cases were delisted. Cases with “0” responses are to be excluded from the further analysis as irrelevant data too. After the data revision there are 194 cases left in the dataset. Although the distribution is still negativeley skewed we may observe the distribution is closer to normal in terms of kurtosis. (Appendix 2, Picture 1a, Table 1c). We checked the significance of non normal distribution by comparing the numeric value of kurtosis with twice the Std. Error of kurtosis. Looking at the range from minus twice the Std.Error of kurtosis to plus twice the Std.Error of kurtosis, we see that the kurtosis value falls within this range. Thus the non normal distribution is considered to be insignificant. The JSL variable was also tested for the the distrubution normality depending on “Branch” and “Work Exp” variables. (Appendix, Histogram). Descriptive statistics of......

Words: 2253 - Pages: 10

Bus 308 Week 3 Anova and Paired T-Test

...3 ANOVA and Paired T-test Click Link Below To Buy: http://hwcampus.com/shop/bus-308-week-3-anova-paired-t-test/ 1Week 3 ANOVA and Paired T-test At this point we know the following about male and female salaries. a. Male and female overall average salaries are not equal in the population. b. Male and female overall average compas are equal in the population, but males are a bit more spread out. c. The male and female salary range are almost the same, as is their age and service. d. Average performance ratings per gender are equal. Let's look at some other factors that might influence pay - education(degree) and performance ratings. 1 Last week, we found that average performance ratings do not differ between males and females in the population. Now we need to see if they differ among the grades. Is the average performace rating the same for all grades? (Assume variances are equal across the grades for this ANOVA.) You can use these columns to place grade Perf Ratings if desired. A B C D E F Null Hypothesis: Alt. Hypothesis: Place B17 in Outcome range box. Interpretation: What is the p-value: Is P-value < 0.05? Do we REJ or Not reject the null? If the null hypothesis was rejected, what is the effect size value (eta squared): Meaning of effect size measure: What does that decision mean in terms of our equal pay question: 2 While it appears that average salaries per each grade differ, we need to test this assumption.......

Words: 1045 - Pages: 5

Bus 308 Week 3 Anova and Paired T-Test

...3 ANOVA and Paired T-test Click Link Below To Buy: http://hwcampus.com/shop/bus-308-week-3-anova-paired-t-test/ 1Week 3 ANOVA and Paired T-test At this point we know the following about male and female salaries. a. Male and female overall average salaries are not equal in the population. b. Male and female overall average compas are equal in the population, but males are a bit more spread out. c. The male and female salary range are almost the same, as is their age and service. d. Average performance ratings per gender are equal. Let's look at some other factors that might influence pay - education(degree) and performance ratings. 1 Last week, we found that average performance ratings do not differ between males and females in the population. Now we need to see if they differ among the grades. Is the average performace rating the same for all grades? (Assume variances are equal across the grades for this ANOVA.) You can use these columns to place grade Perf Ratings if desired. A B C D E F Null Hypothesis: Alt. Hypothesis: Place B17 in Outcome range box. Interpretation: What is the p-value: Is P-value < 0.05? Do we REJ or Not reject the null? If the null hypothesis was rejected, what is the effect size value (eta squared): Meaning of effect size measure: What does that decision mean in terms of our equal pay question: 2 While it appears that average salaries per each grade differ, we need to test this assumption.......

Words: 1045 - Pages: 5