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What are the advantages of quantitative techniques?
Quantitative techniques allow for data-driven decision-making, providing objective and measurable results. They can help identify trends, patterns, and relationships in data that may not be obvious through qualitative analysis alone. Additionally, quantitative techniques can be used to make predictions and forecasts based on statistical models.
What type of data is movie ratings?
Movie ratings can be considered as ordinal data, as they are often ranked or categorized based on a predefined scale (such as stars or numerical values).
Do surveys tend to gather qualitative or quantitative data What types of information are commonly measured with surveys?
Surveys can gather both qualitative and quantitative data, depending on the type of questions asked. Quantitative data is more common in surveys and typically measures things like demographics, preferences, satisfaction levels, and opinions. Qualitative data may also be collected through open-ended questions to capture more detailed or subjective responses.
Which sociological research method is most likely to produce quantitative data that will identify cause and effect relationships?
Experimental research methods are most likely to produce quantitative data that can identify cause and effect relationships in sociology. This involves manipulating variables and observing the effects on outcomes.
What two categories can research be divided into?
Research can be divided into two main categories: qualitative research, which focuses on understanding the "why" and "how" behind phenomena through qualitative data analysis; and quantitative research, which focuses on collecting and analyzing numerical data to answer research questions through statistical methods.
Data at the ordinal level are quantitative only?
This statement is absolutely False due to the fact that quantitative level consist mainly in numeric situations.
Is the category of ages nominal or ordinal data?
Neither, age is at a ratio level of measurement.
IS GPA nominal data or ordinal?
It is ordinal.
What is ordinal statistics?
Ordinal statistics or data is classified as ordinal if the values can be rated on a scale or put i order. Ordinal data can be counted but never measured.
Is asking your birth year a ordinal data?
No, but the answers provide ordinal data.
Is Gender nominal or ordinal?
Gender is nominal. Nominal is categorical only; no ordering scheme. Ordinal level of measurement places some order on the data, but the differences between the data can't be determined or are meaningless.
Which level of measurement is required for the median?
It can be computer for ordinal level data or higher. It is NOT effected by extremely large or small numbers
What is an ordinal graph?
An ordinal graph is a type of graph used in data visualization that represents ordered categories or rankings. In this graph, the x-axis typically represents the ordinal categories, while the y-axis displays a quantitative measure associated with each category. Unlike nominal graphs, which depict unordered categories, ordinal graphs emphasize the inherent order of the categories, making them useful for showing trends and comparisons within ranked data. Common examples include bar charts and line graphs that illustrate ordinal data such as ratings or rankings.
What is the similarities between quantitative data and quantitative data?
don't you mean quantitative data and qualitative data?
Are data at nominal level of measurement quantitative or qualitative?
This kind of data is qualitative, meaning it is an observation of a particular facet of the observed thing. Quantitative date is numerically-based.
Why is ANOVA used for interval and ratio level data only and not used for nominal or ordinal level data?
ANOVA (Analysis of Variance) is used for interval and ratio level data because it relies on the assumption that the data is continuous and normally distributed, allowing for meaningful calculations of means and variances. Nominal and ordinal data do not meet these criteria; nominal data consists of categorical variables without a numerical relationship, while ordinal data has a ranked order but does not provide equal intervals between ranks. Consequently, ANOVA is not appropriate for these data types as it cannot accurately assess differences in means or variances.
Can a A set of ordinal interval or ratio level data have one mode?
Yes, a set of ordinal, interval, or ratio level data can have one mode, which is the value that appears most frequently in the dataset. In ordinal data, the mode represents the most common category, while in interval or ratio data, it reflects the most frequently occurring numerical value. However, it is also possible for such datasets to have no mode or multiple modes, depending on the distribution of the values.
