This mini-site combines four prior pages into one site: an informational page, an iPhone model datagrid summary, an SBU basketball data page, and a consumer click behavior analysis. Use the buttons above to switch pages.
Purpose
Consolidate existing analysis and data into a consistent, minimal website. Each page reproduces key content sections from the original files while keeping layout and styling consistent across pages.
Contents
Home — Project overview and navigation.
iPhone Data — Selected iPhone model comparison table and interactive summary area.
SBU Basketball — Season statistics excerpt and context.
Click Behavior — Consumer click behavior and conversion rate analysis (text excerpt from your uploaded page).
iPhone Model Comparison
Selected estimates and short summaries. Core column: Estimated Global Sales (millions).
Model
Release Year
Estimated Global Sales (millions)
Typical Price Range (USD)
Battery (mAh)
Form Factor
iPhone 6 / 6 Plus
2014
222.4
$199 - $749
1810
4.7" / 5.5"
iPhone 11
2019
159.2
$699 - $849
3110
6.1" / Dual-camera
iPhone XR
2018
77.4
$599 - $749
2942
6.1" / LCD
iPhone 12 series (cumulative)
2020
100.0+
$699 - $1,099
2815
various sizes / OLED
Click any table row to show a short summary here.
SBU Basketball — Data Analysis
Overview
Stony Brook University has produced several standout players and experienced notable highs over the past two decades. The table below is an excerpt of season statistics used to analyze wins, losses, and scoring trends.
Season stats (excerpt)
Season
Conference
W
L
Win %
PS/G
PA/G
2025-26
CAA
14
9
.609
72.6
70.5
2024-25
CAA
8
24
.250
66.5
74.1
2023-24
CAA
20
15
.571
73.5
72.3
2021-22
AmEast
18
13
.581
72.9
73.1
Consumer Click Behavior & Conversion Rate
Summary and practical implications for website analytics and optimization.
Purpose
This page helps students and business professionals understand consumer click behavior and conversion rates, and how those metrics can be used to improve website performance and user experience.
Key Ideas
Click behavior shows how users interact with a site — which pages they visit, what controls they click, and time on page.
Conversion rate measures how many users complete a desired action (purchase, sign-up, etc.).
More clicks do not always equal better outcomes — high click activity can indicate confusion or distraction rather than intent.
Data Sources & Metrics
Raw data typically comes from analytics platforms (Google Analytics, server logs) and includes page views, click counts, bounce rates, and conversions. Visualizations such as funnel diagrams clarify where users drop off between discovery and conversion.
Practical Recommendations
Simplify page design to reduce distractions and focus user attention on the core action.
Make calls-to-action more visible and explicit.
Optimize and shorten checkout or sign-up flows to reduce drop-off.
Use A/B testing to compare designs and measure causal impact on conversion rate.
Conclusion
Analyzing click behavior alongside conversion rate provides stronger, actionable insights than examining either metric in isolation. Combining behavioral data with conversion outcomes lets teams identify friction points and test targeted improvements.