SPSS is the premier statistical analysis software, and has been the industry benchmark for decades. It is practically impossible to do work in the social sciences without understanding the basic uses and functions of SPSS. As the full name of the software (Statistical Package for the Social Sciences) suggests, the suite is especially designed for use in the social sciences and has become standardized in some fields like psychology (Field, 2005). Researchers can use SPSS to input the raw data from their research designed and the software can compute a practically limitless set of statistics based on those raw figures and inputs. Basic descriptive statistics such as frequency and rates of distribution are obviously available, as are various ratios that can be drawn from the data. Simple correlations can therefore be drawn. However, there are many more robust uses for the software including the ability to run some of the most sophisticated analytic techniques that ensure the reliability and validity of the research. These techniques include an Analysis of Variance (ANOVA), bivariate correlations, t-tests, chi-tests and more. Regression analyses, factor analyses, and two-step cluster analyses are also possible using SPSS (IBM, 2013). It is impossible to imagine computing the data gleaned from research in any other way, although there are competing products on the market. The vast majority of researchers and analysts in the educational, "think tank," and corporate sectors are
Statistics provides us with very useful tools and techniques that aide us in dealing with real world scenarios. I have been able to learn several useful concepts by studying statistics that can aide me in making rational and informed decisions that are supported by the analysis results. Statistics as a discipline is the application and development of various processes put in place to gather, interpret, and analyse the information. The quantification of biological, social, and scientific phenomenons, design and analysis of experiments and surveys, and application of
Assume 20% of all email is spam. A large Internet provider plans on conducting a survey of 900 emails to see what percentage are spam.
Consider the following scenario in answering questions 5 through 7. In an article appearing in Today’s Health a writer states that the average number of calories in a serving of popcorn is 75. To determine if the average number of calories in a serving of popcorn is different from 75, a nutritionist selected a random sample of 20 servings of popcorn and computed the sample mean number of calories per serving to be 78 with a sample standard deviation of 7.
3. Questions 3a through 3d are based on a distribution of scores with and the standard Draw a small picture to help you see what is required.
The quantitative research is also based on statistical reports on correlations, regression analysis, comparisons of means and variances, and statistical significance of findings.
To view the research on a nominal scale, the research data can be drawn from the type of class. The word nominal is derived from the root word in Latin for name (Usable Stats, 2013). The name of the class, Psychological Statistics, is the nominal measurement for this research. When conducting this study, the study will only be measured during the course of this specific class. The results could drastically change when considering another type of class such as Quantitative Literacy as the cognitive understanding of such a collegic math class may be more optimal through a different course-delivery format.
Assuming unequal variances, the two sampled t-Test was applied on the data sets of female and male shoe sizes with the alpha value of 0.05. The null hypothesis was that the female and male shoe sizes have an equal mean while the alternative hypothesis was that female and male shoe sizes do not have an equal mean. With the degrees of freedom being 27, the t-statistic is -8.16. The probability that -8.16 is ≤ -1.70 is 4.5×10-9 for the one-tailed test. Also, the probability that -8.16 is ≤ ±2.05. is 9.1×10-9 for the two-tailed test. Given that both probabilities are under the alpha value of 0.05, the null hypothesis is therefore rejected, and the alternative hypothesis is accepted at the 95% confidence level.
Read the directions and write answers independently. 1. (L.2) Choose the sentence with correct capitalization and punctuation. A. Mrs. Brown catches the bus at the corner of Elm and N. Grove.
The 95% confidence interval indicates that since 1995 the average age of tourists has increased between 0.85 and 4.69 years.
What do these variables represent (i.e., what information/question is being asked and answered for each variable)? In order to provide a complete and appropriate answer to this question, you will need to look at the variable labels and values (response options) in the SPSS file and the GSS codebook for additional information (i.e., what missing categories are available for coding, what year(s) was/were these questions asked). {Remember: Just because I am not asking you for descriptives and frequency tables does not mean that you shouldn’t run them to look at the distribution of responses. That information may be helpful in answering this
1The purpose of this paper is to perform a chi-square analysis after watching the assigned video. Data taken from a given table will be entered on the SPSS data set with intend to obtain an output. The cross-tabulation table will be highlighted in the output document. Then the highlighted output will be submitted to the instructor.
h) Is the aspirin produced by a particular pharmaceutical company better than that of a competitor at relieving headaches? Which of the following would best be used to study this: 1) a case-controlled observation; 2) an observation; 3) a double-blind experimental procedure; and 4) and experimental
MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Use the given degree of confidence and sample data to construct a confidence interval for the population proportion. 1) Of 346 items tested, 12 are found to be defective. Construct a 98% confidence interval for the percentage of all such items that are defective. A) (3.34%, 3.59%) B) (1.18%, 5.76%) C) (1.85%, 5.09%) D) (0.93%, 6.00%) E) (0.13%, 6.80%) 2) Of 81 adults selected randomly from one town, 64 have health insurance. Construct a 90% confidence interval for the percentage of all adults in the town who have health insurance. A) (71.6%, 86.5%) B) (67.4%, 90.7%) C) (70.1%, 87.9%) D)
In this mathematical circumstance, it is appropriate to use the Normal Model with this data distribution because of how roughly symmetric and unimodal. The summary statistics for the OB Math SAT scores are as follow: the number of values is 287, the mean of the data is 553.62369, the standard deviation is of approximately 65.984512, the median of the data is 540, the range of the data is 390, the minimum value is 360, the maximum value is 750, the first quartile of the data is 510, and the second quartile of the data is 590. To calculate the percent of students that had an SAT math score higher than 560, I used the z-score formula which is z-score= raw score- mean/ standard deviation and plugged the values for each variable. After
Statistical Product and Service Solutions for Windows (SPSS) 12.0 software package and SAS 8.0 software. SPSS 12.0 was used for all statistical analysis except linear regression which used SAS 8.0.