Statistical Techniques Exploration

What is the primary difference between quantitative and qualitative data?

• Quantitative data is descriptive; qualitative data is numerical.

• Qualitative data can be measured in units like meters or liters.

• Quantitative data is numerical; qualitative data is descriptive.

• Quantitative data is always more accurate than qualitative data.

Name a common statistical technique used for analyzing quantitative data.

• Regression analysis

• ANOVA

• Chi-square test

• T-test

What statistical method would you use to find the average of a dataset?

• Mode

• Standard Deviation

• Mean

• Median

Define the term 'standard deviation' in the context of data analysis.

• Standard deviation is the average of a set of data values.

• Standard deviation indicates the highest value in a dataset.

• Standard deviation is a measure of the dispersion or spread of a set of data values around the mean.

• Standard deviation measures the total number of data points in a dataset.

What is a histogram and what type of data does it represent?

• A histogram is used for displaying text data.

• A histogram represents continuous numerical data.

• A histogram represents categorical data.

• A histogram only represents discrete data.

Explain the purpose of a t-test in statistical analysis.

• The purpose of a t-test is to compare the means of two groups to see if they are statistically different from each other.

• To analyze the variance within a single group.

• To determine the correlation between two variables.

• To calculate the median of a single group.

What is the significance of a p-value in hypothesis testing?

• The p-value measures the effect size of the observed results.

• The p-value indicates the probability of obtaining test results at least as extreme as the observed results, assuming the null hypothesis is true.

• A p-value below 0.05 guarantees the null hypothesis is false.

• The p-value indicates the strength of the alternative hypothesis.

Describe what a correlation coefficient indicates about two variables.

• A correlation coefficient measures the average of two variables.

• A correlation coefficient indicates the absolute difference between two variables.

• A correlation coefficient shows the causation between two variables.

• A correlation coefficient indicates the strength and direction of the relationship between two variables.

What statistical technique would you use to analyze survey responses?

• Time series analysis

• Qualitative analysis

• Descriptive and inferential statistics

• Regression analysis

How can regression analysis be used in data analysis?

• To eliminate outliers from the dataset

• To create visualizations of data only

• To summarize data without any analysis

• Regression analysis can be used to model relationships between variables, predict outcomes, and assess the impact of one variable on another.