
Independent Samples T-Test
Independent Samples T-Test SHARE THE ARTICLE ON Share on facebook Share on twitter Share on linkedin Table of Contents What is a T-Test? Before we
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We’ve been avid users of the Voxco platform now for over 20 years. It gives us the flexibility to routinely enhance our survey toolkit and provides our clients with a more robust dataset and story to tell their clients.
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Explore Voxco
Need to map Voxco’s features & offerings? We can help!
We’ve been avid users of the Voxco platform now for over 20 years. It gives us the flexibility to routinely enhance our survey toolkit and provides our clients with a more robust dataset and story to tell their clients.
Steve Male
VP Innovation & Strategic Partnerships, The Logit Group
Explore Regional Offices
Survey analysis, as the name suggests, refers to the process of analyzing survey results from customers, employees, or others. It is used to draw conclusions from the data gathered from surveys. It is a cost-effective method to study customer preferences and behavior as it is often impossible to survey everyone in your target population.
Statistical survey analysis is important as it allows you to draw inferences and generalisations of your whole target audience through the sampling of a small subset of this population. Responses and statistical information alone does not benefit a company. It’s the inferences, trends, and patterns that they identify within these responses that help them make better decisions.
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The following are some popular types of statistical survey analysis methods:
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Customer Loyalty in some form can be seen as a ladder of commitment for a customer. These stages in the ladder increase the loyalty of a customer as they move up.
Learn how to meet respondents where they are, drive survey completion while offering a seamless experience, Every Time!
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Regression analysis includes a set of statistical methods employed in the estimation of the relationships between a dependent variable with one or more independent variable(s). This method of analysis mathematically sorts out which variables have the most impact, and the way these variables interact with each other. It is a useful method when trying to define the impact of a change in your independent variable.
Regression analysis is conducted by gathering data on the variables in question. Then, this information is plotted on a graph/chart. Graphs resulting from regression analysis depict a regression curve that reflects the relationship between the variables.
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Survey organizations around the world have maximized their phone survey ROI with the advanced features, hosting options, seamless telephony integration, and flexible pricing of our CATI software.
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ANOVA test, or analysis of variance test, is used in amalgamation with regression studies in order to identify the effect of independent variables on dependent variables. It can compare a range of variable groups simultaneously to see if there are any corrections between them.
There are two main types of ANOVA tests:
There are also variations of the ANOVA test, such as MANOVA. MANOVA, or multivariate analysis of variance, is used to compare multivariate sample means. It helps determine differences between independent groups on more than one continuous dependent variable.
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Conjoint analysis is used in market research to determine how people value different attributes of a product or service, in order to help organizations understand customer preferences and cater to their needs and wants more effectively. It is a survey-based statistical technique that is conducted by breaking a product/service down to its attributes, or features, and testing different combinations of these attributes to identify consumer preferences.
Survey results can then be used to calculate “preference scores”. This score is a numerical value that measures how much each attribute affected the respondent’s choices to purchase the product. These preference scores are used to build simulators that can forecast the market share for a set of different products offered to the market. This simulator can model respondent decisions and is used to identify specific features and pricing levels that help forecast potential demand in the competitive market.
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T-Test is a statistical test used to compare the mean of two groups of variables. It is usually used when the data sets come from the same population, follow a normal distribution, and may have unknown variances. It is used as a hypothesis testing tool, which means it allows the testing of assumptions made about certain populations.
When T-Test is used, the following assumptions are made about the data:
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Crosstab analysis, or cross tabulations, involves the use of data tables that display the results of every respondent. It’s a statistical tool used for categorical data and it enables the examining of relationships that may not be apparent when analysing survey responses. Categorical data refers to values that are mutually exclusive to each other.
Crosstab analysis helps organizations make informed decisions by identifying patterns, correlations, and trends between the study’s parameters.
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