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ANOVA Assignment Help in SPSS
The Analysis of Variance simply known as ANOVA is a statistical tool used in determining whether a set or more of unrelated groups have any statistical significant differences. It specifically tests the null hypothesis by comparing the means between the groups and checking whether they are significantly different from each other. There are two main types of tests that can be done by ANOVA:
- One way test- this test is used when you want to test two groups to determine whether there is a significant difference between them.
- Two-way ANOVA test- This type of test can be with or without replication. Replication means the independent variables are doing more than one thing.
Two-way test without replication, double est a group. It only has one group.
- Two-way ANOVA with replication- Here you have two groups and the members of those groups are doing more than one thing
ANOVA uses the following assumptions while being used in conducting tests;
- There is normal distribution
- The errors are independent
- Expected values of errors are zero
- The variances of all the errors are equal to one another
ANOVA is applied in many disciplines such as commerce where it is used to determine sales of different products and in health where it can determine how effective a drug is. If you have career aspirations in one of these fields then you must make descriptive statistics your best topic of study. You will greatly use ANOVA concepts to organize large data by relating its variables correctly.
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Chi Square Assignments Help in SPSS
Chi Square in statistics is a tool used to determine how expectation compares to results. When conducting a hypothesis test on a Chi square; the test statistic is computed and compared to a critical value. According, to our survey we have realized that 89% of chi-square questions test on factorial analysis in SPSS. In these questions you are required to compare means of two or more factors of your data. A Chi square has two main applications;
- Goodness of fit test
- Test of independence of attributes
- Test for homogeneity
It is only appropriate to use a Chi square test if the following four assumptions are met.
- Independence of observation- cases should not have any relationship
- The groups must be mutually exclusive
- At least 5 expected frequencies must exist in each group of a categorical variable
- There must be a one categorical data
All these assumptions can easily be checked in SPSS.
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Online Statistics Tutorial in SPSS
Statistics entails calculation and manipulation of large data sets. This process requires sophisticated software and complex formulas to perform. Learning statistics is time consuming because of the sheer volume of data and repetition of calculations. Since most of the topics are interrelated students cannot afford to miss a session. Topics such as Confidence intervals are intricate and involving. They are time consuming to catch a break leave alone hanging out with friends. We know that students need time to relax with friends, go to their part time jobs or do other extra curricula activities like playing soccer. That is why we are asking students to take advantage of our online statistics tutor service.
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Statistics is used in many sectors such as weather forecasting, sociology, mathematical science and research. It is highly applicable on contemporary research. Recently, research skills have become hot cakes in all professional arenas. Failing in statistics course can dent your chances of getting that lucrative job you were hoping for. If you are struggling with statistics homework, it is not too late to get help here. Our Tutors are dedicated in helping students understand all the technical theories in statistics. Students through live chat and email can link up with the tutors and get their problems solved.
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Statics Assignment Help Using SPSS
Statistics is the measurement of some attributes of a given data sample. It mainly entails collection, analysis, interpretation, presentation and organization of data. Data is the bedrock of all companies round the world, from media, health sciences, financial forecasting to engineering and design. To manipulate data, one needs to have in depth knowledge of sophisticated software like SPSS. The analysed data can be used in making predictions about the future and assessing the uncertainty of those predictions.
Statistics provide probability tools that are used for prediction and forecasting. Some of the topics covered in statistics include least squares, outliers, statistical significance, factorials, Bayes’ theorem, central limit theorem, prediction interval and regression. Statistics is a branch of mathematics and involves a lot of calculation. Most students tend to think that mathematics is complicated because of the many formulas involved.
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Inferential Statistics Homework help in SPSS
Inferential statistics uses data drawn from a given population to make inferences about that population. It is used to make probability judgement that an observed judgement either happened by chance or is dependable.
Inferential statistics uses the following methods;
- The estimation of parameters- the sample obtained must represent the population. This sample should be randomly picked to avoid bias. The precision of the estimate is highly dependent on the sample size. If one uses a large sample the precision is likely to be high.
- Testing of statistical hypothesis- it is also known as confirmatory data analysis. It tests the validity of a test by determining if it happened by chance. Before conducting the test one has to know the null hypothesis. Null hypothesis is what is expected to be true.
It is impractical to measure every item in a population, thus inferences have to be made from a sample.
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Sample Assignment Help in SPSS
Sampling is the act of selecting a suitable sample using a set method. The method employed depends on the type of analysis to be performed. The methods used include;
- Simple sampling- it is just like random sampling
- Random sampling- everyone in the group has an equal chance of being selected. This is considered the best method of selecting a sample from a population of interest. It eliminates bias, but at the same time it is very difficult to achieve because of the time, effort, and money involved.
- Systematic sampling- Here, an orderly or logical method is used in selecting subjects from a population of interest. This method provides a representative sample but it is very difficult to achieve.
- Stratified sampling-It involves working out the proportions, of the types of people within the population of interest. This method ensures that the target population is highly represented. We can therefore generalise from the results obtained.
- Cluster sampling- In this method, the researcher divides the population of interest into various groups called clusters. A simple random sampling is then conducted on the clusters. Analysis and research are then conducted on the sampled clusters.
There are two main types of sampling;
- Probability sampling- This is a type of sampling where each and every unit within the population of study has an equal chance of making up the sample.
- Non-probability sampling- in this type of sampling some of the items within the target population may not get a chance of being selected.
A sample taken from a population should represent the entire population. To achieve this random sampling method is usually used. Before sampling, it is important to define the population. A population is the people or items with the characteristics that you wish to study. The main purpose of sampling is to learn about a large group who have something in common. Examples of target populations are drug addicts, teenagers, women etc. It is impossible to study every individual in the group so a sample is selected to represent the population, the more the representatives of the group the greater the accuracy level.
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