€25.21 – €28.94
1. Hypothesis: Correlation Between Variables
- Description: There is a statistically significant correlation between
{Variable A}and{Variable B}in the dataset. - Example: In a sales dataset, investigate whether product price impacts sales volume.
2. Hypothesis: Impact of Categories on Outcomes
- Description: The category
{Category A}has a measurable effect on{Outcome Variable}compared to other categories. - Example: In a marketing dataset, test whether email campaigns perform better in specific geographic regions.
3. Hypothesis: Temporal Trends
- Description: The values of
{Variable X}show a consistent upward or downward trend over{Time Period}. - Example: In a financial dataset, analyze whether monthly revenue has increased consistently over the past year.
4. Hypothesis: Presence of Anomalies
- Description: There are significant anomalies or outliers in
{Variable X}that deviate from the expected distribution. - Example: In a sensor dataset, determine if specific readings significantly deviate from normal operational ranges.
5. Hypothesis: Distribution Characteristics
- Description: The distribution of
{Variable Y}follows a{Distribution Type}(e.g., normal, exponential). - Example: In a survey dataset, assess whether customer satisfaction scores are normally distributed.
