Before discussing SPSS processes, it’s important to understand statistics and its significance. Statistics involves using data to analyze and predict trends.
About Statistics
Key Highlights
- Open-source software, meaning its source code is freely available for anyone to modify and distribute.
- Supports multilingual websites, allowing you to create content in multiple languages.
Reading Time
10 minutes
Why to learn statistics?
It may expose the clear preferences or thoughts of a targeted segment of customers. When a company dares to launch a new product, statistical data become their secret weapon to mitigate failure risks; even more, they can cater to customer needs and aggressively capture market share. This is precisely why most forward-thinking companies have established cutting-edge departments dedicated to this cause.
Descriptive Statistics
The so-called data characteristics? They’re merely the beginning. Once you dive into sorting the data, brace yourself for eye-opening revelations about the testers’ genders and their consumption habits. Boring? Think again. This information isn’t just basic—it’s a game-changer.
Inferential Statistics
The overall conclusion derived through data analysis is an eye-opener. The most common method is the hypothesis test, where you either confirm whether H0 (p-value) is less than 0.05 or face the glaring truth. If it is, you’re bound to accept H0 without question; but beware, if it isn’t, H0 faces outright rejection, no excuses.
Conclusion
Harnessing the power of descriptive statistics is not just beneficial, it’s downright crucial. Imagine the irony: a survey confined to a specific area or ethnic group, yet narrative statistics not only turbocharge reader comprehension but also expose the survey’s legitimacy. Picture this: a company eager to dissect perfume preferences among northern women aged 25 to 55, only to be slapped with the cold hard truth—descriptive statistics unveil that while the age fits, the bulk of respondents hail from the south. This analytical blunder renders the data useless, shattering the company’s expectations.
Example:compare the differences between the two
1
30% of international students come from Taiwan.
2
95% of the international students surveyed are satisfied with their life in the UK.
3
About 55% of students in Taiwan will want to study in the UK.
4
70% of students in Taiwan are not sure about the major they want to study in the future.
In the above four sentences, (1) and (2) belong to descriptive statistics; (3) and (4) belong to inferential statistics.
Have you found out any differences?
Inferential sentences will have words with more ambiguous meanings, such as “about”; on the contrary, sentences belong to description will not contain the vague words.