I can't tell you which one is most reliable because data (or information) can be collected in so many different situations to answer different questions. If I am conducting a very scientific experiment, for example I want to know if a type of tomato grows better in an acid soil, then I need to collect and analyze quantitative data.But in many fields, both types of data are needed. Sociology and psychology studies use qualitative data. For example, I want to know if people who have lived in hot climates for long periods of time, are more comfortable with heat and humidity. So I ask people if they are feeling uncomfortable (qualitative data), how long they have lived in a hot climate (quantitative data) , and also recorded the heat and humidity (quantitative data).- See related link. From the third link, the author opines:"What qualitative methods (e.g. case studies and interviews) lose on reliability they gain in terms of validity. They provide a more in depth and rich description."
There is no point in collecting data simply for the sake of collecting data. You need to analyse it: summarise it and use key information from it to make some assessments about the data.
Quantitative Data is only as good as the following: 1)The accuracy of the tools or machines used to measure whatever it is that is obtaining the data. For example, one of the reasons that the calipers to measure bolts for spacecrafts cost the huge amounts we all laugh about is not a laughing matter. The required precision is so high it is not the same as the precision that one might need for a school project! 2) Human error. Somebody is doing the measurements or adding reagents if it is an experiment, and so on. For example, someone came to my home to test the water. They had a type of device that could measure how much color was caused by a reagent added to water. Sounds good right? Not so right. The people did not know how to add water correctly to a test tube so that the correct amount of water mixed with the correct amount of reagent! 3) Computer error. Don't think it does not happen! Despite the drawbacks, overall quantitative data is generally BETTER than qualitative, but it is not perfect. Remeber Apollo 13!
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Quantitative Data is only as good as the following: 1)The accuracy of the tools or machines used to measure whatever it is that is obtaining the data. For example, one of the reasons that the calipers to measure bolts for spacecrafts cost the huge amounts we all laugh about is not a laughing matter. The required precision is so high it is not the same as the precision that one might need for a school project! 2) Human error. Somebody is doing the measurements or adding reagents if it is an experiment, and so on. For example, someone came to my home to test the water. They had a type of device that could measure how much color was caused by a reagent added to water. Sounds good right? Not so right. The people did not know how to add water correctly to a test tube so that the correct amount of water mixed with the correct amount of reagent! 3) Computer error. Don't think it does not happen! Despite the drawbacks, overall quantitative data is generally BETTER than qualitative, but it is not perfect. Remeber Apollo 13!
what education does a cartographer need? and what is cartographer's Subdivisions or specialists ?
If you need a map drawing ask a cartographer, not a cartoonist.
A cartographer is a professional mapmaker. There are several tools that a cartographer needs to perform the job such as digital cameras and scanners, lighting tables, lettering aids, T-squares and protractors.
Quantilative is where quantitative and qualitative data start to blur. You can ask a question in a quantitative fashion (survey question) but if you have a small sample size, then you need to interpret the data qualitatively (e.g., few, some, most) as opposed to quantitatively (e.g., 10%). it can go the other way as well. If you have a qualitative exercise (e.g., highlighter exercise) that you deploy to a large sample size, you can interpret that data quantitatively (e.g., % who selected a certain area of the image).
To classify you NEED to go to this website it can really help. GOOGLE.COM
Scientists call information collected from observations data. Data can be qualitative (descriptive) or quantitative (numerical), and it is analyzed and used to draw conclusions or make predictions in scientific research.
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To capture data in a manual AIS, you would need to physically input transaction information into journals or ledgers. Records would need to be organized based on predefined categories to classify them properly. Summarizing involves creating trial balances or financial statements by manually calculating totals and balances. Reporting data would require creating customized reports using the summarized information to provide insights for decision-making.
Because there are sometimes multiple meanings for words such as mole (face, animal) and you need to know which is which so they classify it.
Classification helps to organize and categorize data into different groups based on their characteristics or attributes. This enables easier data analysis, retrieval, and decision-making. It also helps in identifying patterns, trends, and relationships within the data.
Grrr i need help to know what does it mean to classify a real number and how you do it i have hw due tommorow
There is a few properties that needs to be classify for seeding into groups. You will have to pick out and then group together.