📊 Data types are fundamental in statistical analysis to understand phenomena or processes.
📝 Each observation can be a person, business, product, or time period.
🔢 Variables are recorded for each observation, such as age, gender, and preferences.
📊 Nominal level of measurement is the basic level of measurement.
🔢 Nominal data can be summarized using frequency or percentage.
🔢⬆️ Ordinal level of measurement includes variables with a useful order.
📊 There are different types of data: nominal, ordinal, and interval/ratio.
💯 Nominal and ordinal data can be summarized using frequencies.
⚖️ Interval/ratio data is the most precise level of measurement and includes variables that can be measured and categorized.
📊 Data can be represented using different graphical methods based on the level of measurement.
📈 Nominal data is best represented using a bar chart or a pie chart.
📉 Interval/ratio data is best represented using a bar chart or a line graph.
📋 Summary statistics can be presented using frequency tables.
📝 Different types of data can be used in market research to develop new products.
📊 Different types of data: nominal, ordinal, and interval/ratio.
🍫 Preference for types of chocolate: dark, milk, and white.
📈 Measuring satisfaction and likelihood to purchase using ordinal data.
📊 Data can be classified into different types: nominal, ordinal, and interval/ratio.
📉 Nominal data includes categories or labels that cannot be ordered or ranked.
📈 Ordinal data represents data that can be ordered or ranked.