Showing posts with label process. Show all posts
Showing posts with label process. Show all posts
Monday, October 10, 2016
The process of data analysis
The process of data analysis
The process of data analysis
Data analysis is a process for obtaining raw data and converting it into information useful for decision-making by users. Data is collected and analyzed to answer questions, test hypotheses or disprove theories.
There are several phases that can be distinguished. The phases are iterative, in that feedback from later phases may result in additional work in earlier phases.
Statistician John Tukey defined data analysis in 1961 as: "[P]rocedures for analyzing data, techniques for interpreting the results of such procedures, ways of planning the gathering of data to make its analysis easier, more precise or more accurate, and all the machinery and results of (mathematical) statistics which apply to analyzing data."
Data requirements
The data necessary as inputs to the analysis are specified based upon the requirements of those directing the analysis or customers who will use the finished product of the analysis. The general type of entity upon which the data will be collected is referred to as an experimental unit (e.g., a person or population of people). Specific variables regarding a population (e.g., age and income) may be specified and obtained. Data may be numerical or categorical (i.e., a text label for numbers).
Data collection
Data is collected from a variety of sources. The requirements may be communicated by analysts to custodians of the data, such as information technology personnel within an organization. The data may also be collected from sensors in the environment, such as traffic cameras, satellites, recording devices, etc. It may also be obtained through interviews, downloads from online sources, or reading documentation.
Data processing
Data initially obtained must be processed or organized for analysis. For instance, this may involve placing data into rows and columns in a table format for further analysis, such as within a spreadsheet or statistical software.
Data cleaning
Once processed and organized, the data may be incomplete, contain duplicates, or contain errors. The need for data cleaning will arise from problems in the way that data is entered and stored. Data cleaning is the process of preventing and correcting these errors. Common tasks include record matching, deduplication, and column segmentation. Such data problems can also be identified through a variety of analytical techniques. For example, with financial information, the totals for particular variables may be compared against separately published numbers believed to be reliable. Unusual amounts above or below pre-determined thresholds may also be reviewed. There are several types of data cleaning that depend on the type of data. Quantitative data methods for outlier detection can be used to get rid of likely incorrectly entered data. Textual data spellcheckers can be used to lessen the amount of mistyped words, but it is harder to tell if the words themselves are correct.
Exploratory data analysis
Once the data is cleaned, it can be analyzed. Analysts may apply a variety of techniques referred to as exploratory data analysis to begin understanding the messages contained in the data. The process of exploration may result in additional data cleaning or additional requests for data, so these activities may be iterative in nature. Descriptive statistics such as the average or median may be generated to help understand the data. Data visualization may also be used to examine the data in graphical format, to obtain additional insight regarding the messages within the data.
Modeling and algorithms
Mathematical formulas or models called algorithms may be applied to the data to identify relationships among the variables, such as correlation or causation. In general terms, models may be developed to evaluate a particular variable in the data based on other variable(s) in the data, with some residual error depending on model accuracy (i.e., Data = Model + Error).
Inferential statistics includes techniques to measure relationships between particular variables. For example, regression analysis may be used to model whether a change in advertising (independent variable X) explains the variation in sales (dependent variable Y). In mathematical terms, Y (sales) is a function of X (advertising). It may be described as Y = aX + b + error, where the model is designed such that a and b minimize the error when the model predicts Y for a given range of values of X. Analysts may attempt to build models that are descriptive of the data to simplify analysis and communicate results.
Data product
A data product is a computer application that takes data inputs and generates outputs, feeding them back into the environment. It may be based on a model or algorithm. An example is an application that analyzes data about customer purchasing history and recommends other purchases the customer might enjoy.
Communication
Once the data is analyzed, it may be reported in many formats to the users of the analysis to support their requirements. The users may have feedback, which results in additional analysis. As such, much of the analytical cycle is iterative. When determining how to communicate the results, the analyst may consider data visualization techniques to help clearly and efficiently communicate the message to the audience.
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Sunday, September 4, 2016
PROCESS TO FOLLOW WHEN LOADING ROM ON MTK PROCESSOR ANDROID DEVICES
PROCESS TO FOLLOW WHEN LOADING ROM ON MTK PROCESSOR ANDROID DEVICES
Android mobile phone are made up different processor depending on company design, needs, market tqrgeting and requirements.
The famous processor for android mobile phones are ;
- Mediatek
- Snapdragon
- Qualcom and more
Today I will teach the process on how to install either STOCK ROM or CUSTOM ROM on MTK processor devices,
If you want to know the different between Stock ROM and Custom ROM please read HERE and also HERE
Before loading any ROM to android devices you are supposed to do the followings
- Backup
- Creating scatter file, in case you meet any problem during loading of ROM and you want to go back,
For creating a backup of your android MTK device using SP Flash tool and MTK Droid tools CLICK HERE
For creating a scatter file on MTK devices CLICK HERE FOR SCATTER
If you will like more custom and stock rom for MTK devices please ANDROID ROM dont forget to register first
For more about mobile phones please go to menu above and browse the submenu of your choice from Rom, applications and games, IOS to Windows phone.
Or chat with me live by clicking chat now from your bottom right corner. or whatsapp only +255757276287 for any ICT problem.
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