# A Quick Guide for Advanced Features

## Introduction

This guide only intends to show the key steps and some advanced features
(such as **cross-tabulation, regression analysis, mean, median, mode, standard deviation**)
that are useful to college students and other users in their survey projects.

Suppose that you are working on a survey project with two goals:

- Understand the relationship between students' sleep and their academic performance, and
- See if gender or sports activities play any role

Let's assume that you plan to use the following four questions in your survey:

**Question 1** How many hours do you sleep on average, on a nightly basis? Please enter a number only.

**Question 2** What is your cumulative GPA, on a 4.0 scale? Please enter a number only.

**Question 3** How much time do you spend on sports on a weekly basis?

- Less than an hour
- 1 - 2 hours
- 2 - 4 hours
- 4 - 6 hours
- More than 6 hours

**Question 4** What is your gender?

- Female
- Male

In this guide, you will accomplish the following tasks:

- Create a survey with questions that collect quantitative, categorical, and ordinal data
- Show mean, median, mode, and standard deviation on these questions
- Perform linear and polynomial regression (with the equation) between two quantitative questions. (Example: time spent sleeping and GPA)
- Conduct two-way cross-tabulation among two categorical variables (Example: Male/Female and time spent playing sports)
- Compare means between groups (Example: Compare mean amount of time spent sleeping each day for Males and Females)

## Questions and Data Types

Each question collects some data from survey participants. The type of data a question collects determines the analysis available to the question. Our website supports three data types:

Data Type | Example | Analysis |
---|---|---|

Categorical | Example 1 – Hair color: Black, Brown, Blonde, etc. Example 2 – Names of people |
Percentage and cross-tabulation |

Ordinal | Example – Strongly agree, Agree, Neutral, Disagree, Strongly disagree | Percentage, mean, median, mode, and cross-tabulation |

Quantitative | Examples – Age, income, blood pressure, temperature, number of people in a family, balance on a bank account, etc. | Mean, media, mode, standard deviation, regression, and comparison of means for categorical and ordinal questions |

Both categorical and ordinal data are also called categorical data.

Suppose that for Question 1 and 2, you plan to collect numbers to conduct regression analysis. To accomplish this task, you have to indicate that the data type of the two questions is quantitative. In addition, we highly recommend that you use validation to require survey participants to only enter numbers in a given range because invalid data will be excluded in analysis. See the following two screenshots:

Suppose that you select Ordinal as the data type for Question 3 and Categorical for Question 4. Please see the following two screenshots:

## Collect Responses

Now you have a survey. The next step is to create a campaign, which allows you specify who can take it, when to start it, etc. For a single campaign, you can create one or multiple distributions. For example, you can post a link to your survey on your Facebook page, or you can send the link to your friends through emails. We allow you to create multiple campaigns and distributions, and you can perform analysis on the responses for any combination of these campaigns and distributions.

## Analysis

Suppose that you have collected enough responses and are ready to perform analysis. Open your survey, click Analyze, Results as shown below:

The above screenshot shows the kinds of data you can use in analysis and the kinds of tools (under "View") available to you. You can look at your data in different views. The default and perhaps the most important view is called "Summary". For Question 1 in the Summary view, if you click "Statistics", you can get the statistics on the responses to this particular question. Please see the following screenshot:

For Question 4 in the Summary view, our website displays the statistics through a chart and table as shown in the following screenshot:

Question 3 is a bit special because its data is ordinal. In the Summary view, you can see the mean, median, and mode in addition to a chart and table. See the following screenshot. Please note that for practical reasons, we calculate the mean for ordinal data. Our wesite automatically assigns 1, 2, etc. to the first row (Less than an hour), second row (1 - 2 hours), etc. when calculating the mean and median.

To perform regression analysis among Question 1 and Question 2, select "Linear Regression" or "Polynomial Regression" under the Results menu and click the Apply button. You'll be prompted to select the independent variable, which must be a quantitative Text Box question. Click the Question menu and select a quantitative Text Box question. Suppose we select Question 1 as the independent variable. Click the Apply button, and you'll get the following chart and equation:

In order to perform cross-tabulation, select "By a Multiple Choice Quesiton" under the Results menu and click the Apply button. You'll be prompted to select a Multiple Choice question. Click the Question menu and select a Multiple Choice question. Suppose we select Question 4 as shown below:

Click the Apply button, and you'll accomplish these two tasks: cross-tabulation among two categorial questions and comparison of means for the selected categorical question.

The above screenshot is equivalent to the following two tables:

Less than an hour | 1 - 2 hours | 2 - 4 hours | 4 - 6 hours | More than 6 hours | |
---|---|---|---|---|---|

Female | 1, 12.50%, 6.67% | 2, 25.00%, 13.33% | 2, 25.00%, 13.33% | 2, 25.00%, 13.33% | 1, 12.50%, 6.67% |

Male | 1, 14.29%, 6.67% | 2, 28.57%, 13.33% | 4, 57.14%, 26.67% |

Mean, Median, Mode | |
---|---|

Female | 3.00, 3, 1 - 2 hours |

Male | 3.29, 4, 4 - 6 hours |

The above screenshot is equivalent to the following table:

Mean of Sleep Hours | |
---|---|

Female | 5.31 |

Male | 4.93 |

The above screenshot is equivalent to the following table:

Mean of GPA | |
---|---|

Female | 3.48 |

Male | 3.46 |

## Data Export

In case the various analytical tools shown above don't satisfy your needs, you can export all individual responses to your survey into an Excel file. Click the Results menu, select Individual Responses, and click the Apply button, which will display a list of individual responses. Then, click the Export menu and the download format. The download will start immediately. Please note that if you have a lot of responses, the download may take a while because data is extracted from various sources in the system backend and is assembled as individual responses. The good news is that you can leave the download window open and start another browser window to continue using our website without waiting for the download to finish.

## We Can Help

We offer many powerful and innovative tools for online surveys, and you have to sign up to access them. All tools and services at AllCounted are completely free. If you have any questions or suggestions, please don't hesitate to contact us at support@allcounted.com.

If your colleagues, friends, or classmates need to do online surveys, please let them know that we can help. Thank you!