Presentation on theme: "Rosseni Din Muhammad Faisal Kamarul Zaman Nurainshah Abdul Mutalib."— Presentation transcript:
Rosseni Din Muhammad Faisal Kamarul Zaman Nurainshah Abdul Mutalib
Why? To describe the sample To check the assumption To address specific research questions
How? Frequencies Descriptives Explore
Frequencies Categorical variables E.g. Male vs Female
Descriptives Continous variables Provides: Mean Median Standard deviation Provides info on distribution of scores Skewness Kurtosis Searching for missing data
Normality Symmetrical, bell-shaped curve Greatest frequencies in the middle and smaller are toward the extreme Obtained by skewness and kurtosis values Histogram can also be used
Outliers Histogram Look at the tails of the distribution Boxplot Look at the little circles with number attached Check whether it is an error or not
Descriptive Statistic Descriptive statistic used to give a systematic general idea using Frequency, Mean and others. This test is only used to report frequencies and percentages involved in the researches conducted. The steps are:
1.Click Analyze, Descriptive Statistics and choose Frequency
2. This will be displayed:
3. Move the variables that you want to look at the frequencies
4. Click Charts and choose any tye of charts that you wanted to use, then click ok
5. This will be the result:
6. Or like this:
7. Maybe like this:
Data normality test in general, it is used for inferential statistic. The procedures are: 1. Click Analyze, Descriptive Statistics and choose EXPLORE.
2. Choose the variable that you want and then move them to Dependent List box
3. in Label Cases by box, put your independent Variable
4. In Display, make sure both (Dependent dan Independent) is chosen.
5. For Statistic choices, choose Descriptive and Outliers
6.for Plot, under descriptive, choose Histogram. click Normality Plots with test. Then click Continue
7.For Option, in Missing Value section, choose Exclude Cases pairwaise. Click continue then OK
8. The output will be like this: Tests of Normality Kolmogorov-Smirnov a Shapiro-Wilk StatisticdfSig.StatisticdfSig. variabel.x a. Lilliefors Significance Correction for Kolmogorof- Smirnov table, we are given information about data normality value. When the value shows non signifikan value ( value > 0.05) this shows that the data is normal
To look for OUTLIERS from the normality test procedures, we can also look for outliers in our data. This can be done using Boxplot. It is shown in small circle with number outside the boxplot as shown in the next slide:
Example of data that have outliers In this case, there are 2 data which is categorized as outliers which is respondent number 177 dan 117. in order to eliminate them we need to go back and delete this 2 data.
Money Isn’t an Issue! Topics With ParentsRelative % Frequency Everything45% Academics29% Social Life17% Lets Parents Talk6% Money3% Total100% Only 3% of students talk with their parents about money. Are USD students that well off?
YOUR LIFE Do you value YOUR LIFE? Times With Drunk Driver Relative % Frequency Cumulative % Frequency 10+26% %31% %42% %60% 040%100% Total100% 60% of USD students have gotten inside a car with a drunk driver. What does this say about our respect for life?
Normal is the New Skinny Number of Breakfasts Weight Under0%11% 6% Normal71%89%68%80% Over29%0%21%14% Grand Total100% Of the students that eat 0 or 1 breakfast a week, 0% are under weight. Ironically, the under weight eat.
Car or Education: What’s More Important? The less money received for an education, the more money spent on a vehicle.
Money, Money, Money USD’s tuition is $200,000 for four years. 42% of students are paying without assistance for an education that they could spend on a Ferrari.
Will we live in a virtual reality? Mean Standard Error Median1.5 Mode2 Standard Deviation Sample Variance Kurtosis Skewness Range7 Minimum0 Maximum7 Sum Count65 USD students spend 90 minutes on social networks a day. How will future generations learn to socialize?
Hands-on exercise Use survey3ED.sav from OR beginners/ beginners/
Procedure for Creating a bar graph 1. Graphs > Legacy Dialogs > Bar > Clustered 2. In Data in Chart are section, click on Summaries for groups of cases > click Define 3. In the Bars represent box click Other summaries function - click on the continuous variable of interest (e.g. total perceived stress). Click on the arrow button The variable should appear in the box listed as Mean (Total Perceived Stress). This indicates that the mean on the Perceived Stress Scale for the different groups will be displayed
Procedure for Creating a bargraph 4. Click on your first categorical variable (eg agegp3). Click on the arrow button to move it into the Category Axis box. This variable will appear across the bottom of your bar graph (x axis). 5. Click on another categorical variable (eg sex). Click on the arrow button to move it into the Define clusters by: box. This variable will be represented in the legend 6. OK