Linear Regression Simulations

Data Generation Results

Scatter Plot with Regression Line

Histogram of Slopes and Intercepts

{% if slope_extreme is defined and slope_extreme is not none %}

Proportion of slopes more extreme than observed slope: {{ slope_extreme | round(4) }}

{% endif %} {% if intercept_extreme is defined and intercept_extreme is not none %}

Proportion of intercepts more extreme than observed intercept: {{ intercept_extreme | round(4) }}

{% endif %}

Parameter to Test: --Select Parameter-- Slope Intercept

The null hypothesis will use the parameter value specified during data generation.

Type of Test: --Select Test Type-- Greater than ( > ) Less than ( < ) Not equal to ( ≠ )

Run Hypothesis Testing

{% if plot3 %}

Hypothesis Testing Results

Parameter Tested: {{ parameter.capitalize() }}

Observed {{ parameter.capitalize() }}: {{ observed_stat | round(4) }}

Hypothesized Value (H₀): {{ hypothesized_value }}

p-value: {{ p_value | round(4) }}

{% if fun_message %}

{{ fun_message }}

{% endif %} {% endif %}

Confidence Intervals

Parameter for Confidence Interval: --Select Parameter-- Slope Intercept

Confidence Level (%): --Select Confidence Level-- 90% 95% 99%

Calculate Confidence Interval

{% if plot4 %}

Confidence Interval Results

{{ confidence_level }}% Confidence Interval for {{ parameter.capitalize() }}: [{{ ci_lower | round(4) }}, {{ ci_upper | round(4) }}]

Mean Estimate: {{ mean_estimate | round(4) }}

Confidence Interval Includes True Parameter: {{ includes_true }}

{% endif %}