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As a kid I always loved information

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that I could get from data

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and the stories that could be told
with numbers.

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I remember, growing up,
I'd be frustrated

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at how my own parents
would lie to me using numbers.

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"Talithia, if I've told you once
I've told you a thousand times."

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No dad, you've only told me 17 times

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and twice it wasn't my fault.
(Laughter)

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I think that is one of the reasons
I got a Ph.D. in statistics.

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I always wanted to know,

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what are people trying to hide
with numbers?

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As a statistician,

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I want people to show me the data

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so I can decide for myself.

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Donald and I were pregnant
with our third child

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and we were at about 41 and a half weeks,

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what some of you may refer to
as being overdue.

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Statisticians, we call that

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being within the 95 percent
confidence interval.

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(Laughter)

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And at this point in the process

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we had to come in every couple of days

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to do a stress test on the baby,

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and this is just routine,

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it tests whether or not the baby
is feeling any type of undue stress.

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And you are rarely, if ever,
seen by your actual doctor,

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just whoever happens to be
working at the hospital that day.

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So we go in for a stress test
and after 20 minutes

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the doctor comes out and he says,

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"Your baby is under stress,
we need to induce you."

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Now, as a statistician,
what's my response?

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Show me the data!

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So then he proceeds to tell us

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the baby's heart rate trace
went from 18 minutes,

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the baby's heart rate was
in the normal zone

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and for two minutes
it was in what appeared to be

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my heart rate zone and I said,

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"Is it possible that maybe
this was my heart rate?

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I was moving around a little bit,

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it's hard to lay still on your back,

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41 weeks pregnant for 20 minutes.

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Maybe it was shifting around."

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He said, "Well, we don't want
to take any chances."

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I said okay.

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I said, "What if I was at 36 weeks

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with this same data?

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Would your decision be to induce?"

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"Well, no, I would wait
until you were at least

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38 weeks, but you are almost 42,

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there is no reason
to leave that baby inside,

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let's get you a room."

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I said,
"Well, why don't we just do it again?

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We can collect more data.

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I can try to be really still
for 20 minutes.

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We can average the two and see

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what that means.
(Laughter)

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And he goes,

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"Ma'am, I just don't want you
to have a miscarriage."

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That makes three of us.

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And then he says,

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"Your chances of having
a miscarriage double

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when you go past your due date.
Let's get you a room."

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Wow. So now as a statistician,
what's my response?

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Show me the data!

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Dude, you're talking chances,

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I do chances all day long,
tell me all about chances.

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Let's talk chances.
(Laughter)

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Let's talk chances.

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So I say, "Okay, great.

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Do I go from a 30-percent 
chance to a 60-percent chance?

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Where are we here
with this miscarriage thing?

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And he goes, "Not quite, but it doubles,

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and we really just want
what's best for the baby."

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Undaunted, I try a different angle.

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I said, "Okay, out of 1,000
full-term pregnant women,

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how many of them are going to miscarry

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just before their due date?

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And then he looks at me
and looks at Donald,

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and he goes, about one in 1,000.

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I said, "Okay, so of those 1,000 women,

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how many are going to miscarry
just after their due date?"

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"About two."
(Laughter)

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I said, "Okay, so you are telling me
that my chances

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go from a 0.1-percent chance

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to a 0.2-percent chance."

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Okay, so at this point
the data is not convincing us

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that we need to be induced,

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and so then we proceed
to have a conversation

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about how inductions lead to a higher rate

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of Cesarean sections, and if at all
possible we'd like to avoid that.

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And then I said,

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"And I really don't think
my due date is accurate."

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(Laughter)

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And so this really stunned him

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and he looked sort of puzzled

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and I said, "You may not know this,

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but pregnancy due dates are calculated

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assuming that you have
a standard 28-day cycle,

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and my cycle ranges —

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sometimes it's 27,
sometimes it's up to 38 —

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and I have been collecting
the data to prove it.

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(Laughter)

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And so we ended up leaving the hospital
that day without being induced.

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We actually had to sign a waiver
to walk out of the hospital.

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And I'm not advocating
that you not listen to your doctors,

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because even with our first child,

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we were induced at 38 weeks;
cervical fluid was low.

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I'm not anti-medical intervention.

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But why were confident to leave that day?

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Well, we had data
that told a different story.

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We had been collecting data for six years.

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I had this temperature data,

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and it told a different story.

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In fact, we could probably pretty
accurately estimate conception.

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Yeah, that's a story you want to tell

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at your kid's wedding reception.
(Laughter)

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I remember like it was yesterday.

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My temperature was a sizzling 97.8 degrees

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as I stared into your father's eyes.
(Laughter)

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Oh, yeah. Twenty-two more years,
we're telling that story.

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But we were confident to leave
because we had been collecting data.

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Now, what does that data look like?

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Here's a standard chart

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of a woman's waking body temperature

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during the course of a cycle.

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So from the beginning
of the menstrual cycle

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till the beginning of the next.

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You'll see that the temperature
is not random.

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Clearly there is a low pattern

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at the beginning of her cycle

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and then you see this jump
and then a higher set of temperatures

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at the end of her cycle.

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So what's happening here?

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What is that data telling you?

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Well, ladies,
at the beginning of our cycle,

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the hormone estrogen
is dominant and that estrogen

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causes a suppression
of your body temperature.

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And at ovulation,
your body releases an egg

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and progesterone takes over,
pro-gestation.

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And so your body heats up in anticipation

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of housing this new little fertilized egg.

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So why this temperature jump?

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Well, think about
when a bird sits on her eggs.

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Why is she sitting on them?

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She wants to keep them warm,

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protect them and keep them warm.

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Ladies, this is exactly
what our bodies do every month,

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they heat up in anticipation

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of keeping a new little life warm.

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And if nothing happens,
if you are not pregnant,

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then estrogen takes back over
and that cycle starts all over again.

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But if you do get pregnant, sometimes you

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actually see another shift
in your temperatures

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and it stays elevated
for those whole nine months.

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That's why you see those pregnant women
just sweating and hot,

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because their temperatures are high.

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Here's a chart that we had
about three or four years ago.

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We were really very excited
about this chart.

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You'll see the low temperature level

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and then a shift and for about five days,

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that's about the time
it takes for the egg to travel

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down the fallopian tube and implant,

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and then you see those temperatures
start to go up a little bit.

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And in fact, we had
a second temperature shift,

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confirmed with a pregnancy test
that were indeed pregnant

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with our first child, very exciting.

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Until a couple of days later

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I saw some spotting
and then I noticed heavy blood flow,

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and we had in fact
had an early stage miscarriage.

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Had I not been taking my temperature

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I really would have just thought
my period was late that month,

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but we actually had data to show

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that we had miscarried this baby,

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and even though this data
revealed a really

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unfortunate event in our lives,

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it was information
that we could then take to our doctor.

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So if there was a fertility issue
or some problem,

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I had data to show:

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Look, we got pregnant,
our temperature shifted,

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we somehow lost this baby.

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What is it that we can do
to help prevent this problem?

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And it's not just about temperatures

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and it's not just about fertility;

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we can use data about our bodies
to tell us a lot of things.

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For instance, did you know that taking
your temperature can tell you a lot

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about the condition of your thyroid?

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So, your thyroid works a lot like
the thermostat in your house.

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There is an optimal temperature
that you want in your house;

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you set your thermostat.

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When it gets too cold in the house,
your thermostat kicks in

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and says, "Hey, we need
to blow some heat around."

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Or if it gets too hot,
your thermostat registers,

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"Turn the A.C. on. Cool us off."

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That's exactly how your thyroid works
in your body.

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Your thyroid tries to keep
an optimal temperature

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for your body.

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If it gets too cold, your thyroid
says, "Hey, we need to heat up."

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If it gets too hot,
your thyroid cools you down.

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But what happens when your
thyroid is not functioning well?

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When it doesn't function, then it shows up

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in your body temperatures,

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they tend to be lower than normal
or very erratic.

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And so by collecting this data

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you can find out information
about your thyroid.

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Now, what is it, if you had a thyroid
problem and you went to the doctor,

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your doctor would actually test

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the amount of thyroid stimulating hormone
in your blood.

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Fine. But the problem with that test is

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it doesn't tell you how active
the hormone is in your body.

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So you might have
a lot of hormone present,

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but it might not be
actively working to regulate

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your body temperature.

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So just by collecting
your temperature every day,

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you get information
about the condition of your thyroid.

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So, what if you don't want to take
your temperature every day?

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I advocate that you do,

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but there are tons
of other things you could take.

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You could take your blood pressure,
you could take your weight —

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yeah, who's excited about

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00:10:48,995 --> 00:10:51,630
taking their weight every day?
(Laughter)

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Early on in our marriage,
Donald had a stuffy nose

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and he had been taking
a slew of medications

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to try to relieve his stuffy nose,
to no avail.

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And so, that night he comes
and he wakes me up and he says,

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"Honey, I can't breath out of my nose."

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And I roll over and I look, and I said,
"Well, can you breath out of your mouth?"

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00:11:16,534 --> 00:11:18,429
(Laughter)

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And he goes,
"Yes, but I can't breath out of my nose!"

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And so like any good wife, I rush him

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to the emergency room

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at 2 o'clock in the morning.

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And the whole time
I'm driving and I'm thinking,

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you can't die on me now.

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We just got married,

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people will think I killed you!
(Laughter)

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And so, we get to the emergency room,
and the nurse sees us,

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and he can't breath out of his nose,

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and so she brings us to the back
and the doctor says,

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"What seems to be the problem?"

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and he goes,
"I can't breath out of my nose."

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And he said,
"You can't breath out of your nose?

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No, but he can breath
out of his mouth. (Laughter)

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00:12:04,698 --> 00:12:07,794
He takes a step back
and he looks at both of us

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and he says,
"Sir, I think I know the problem.

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You're having a heart attack.

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00:12:13,335 --> 00:12:15,285
I'm going to order an EKG and a CAT scan

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00:12:15,285 --> 00:12:17,473
for you immediately."

248
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And we are thinking, no, no, no.
It's not a heart attack.

249
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He can breathe, just out of his mouth.

250
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No, no, no, no, no.

251
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And so we go back and forth
with this doctor

252
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because we think
this is the incorrect diagnosis,

253
00:12:33,519 --> 00:12:36,959
and he's like, "No really, it'll be fine,
just calm down."

254
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And I'm thinking, how do you calm down?

255
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But I don't think
he's having a heart attack.

256
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And so fortunately for us, this doctor
was at the end of the shift.

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So this new doctor comes in,
he sees us clearly distraught,

258
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with a husband who can't breath

259
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out of his nose.
(Laughter)

260
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And he starts asking us questions.

261
00:12:55,789 --> 00:12:59,057
He says, "Well, do you two exercise?"

262
00:13:00,271 --> 00:13:05,732
We ride our bikes,
we go to the gym occasionally.

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00:13:07,548 --> 00:13:09,494
(Laughter)

264
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We move around.

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00:13:12,301 --> 00:13:15,337
And he says, "What were you doing
just before you came here?"

266
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I'm thinking, I was sleeping, honestly.

267
00:13:17,940 --> 00:13:19,994
But okay,
what was Donald doing just before?

268
00:13:19,994 --> 00:13:23,176
So Donald goes into this slew
of medications he was taking.

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He lists, "I took this decongestant
and then I took this nasal spray,"

270
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and then all of a sudden
a lightbulb goes off and he says,

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"Oh! You should never mix this
decongestant with this nasal spray.

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Clogs you up every time.
Here, take this one instead."

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He gives us a prescription.

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00:13:37,714 --> 00:13:40,277
We're looking at each other,
and I looked at the doctor,

275
00:13:40,277 --> 00:13:42,353
and I said,
"Why is it that it seems like you

276
00:13:42,353 --> 00:13:44,517
were able to accurately diagnose
his condition,

277
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but this previous doctor wanted to order

278
00:13:46,605 --> 00:13:48,939
an EKG and a CAT scan?"

279
00:13:48,939 --> 00:13:51,194
And he looks at us and says,

280
00:13:51,194 --> 00:13:55,669
"Well, when a 350-pound man walks in the
emergency room and says he can't breath,

281
00:13:55,669 --> 00:13:57,598
you assume he's having a heart attack

282
00:13:57,598 --> 00:13:59,984
and you ask questions later."

283
00:14:00,877 --> 00:14:05,734
Now, emergency room doctors
are trained to make decisions quickly,

284
00:14:06,145 --> 00:14:09,144
but not always accurately.

285
00:14:09,377 --> 00:14:11,174
And so had we had some information

286
00:14:11,174 --> 00:14:13,608
about our heart health to share with him,

287
00:14:13,608 --> 00:14:16,747
maybe we would have gotten a better
diagnosis the first time.

288
00:14:16,747 --> 00:14:19,543
I want you to consider
the following chart,

289
00:14:19,543 --> 00:14:21,386
of systolic blood pressure measurements

290
00:14:21,386 --> 00:14:25,142
from October 2010 to July 2012.

291
00:14:25,250 --> 00:14:27,175
You'll see that these measurements start

292
00:14:27,175 --> 00:14:30,418
in the prehypertension/hypertension zone,

293
00:14:31,838 --> 00:14:34,287
but over about the course
of a year and a half

294
00:14:34,287 --> 00:14:37,384
they move into the normal zone.

295
00:14:37,384 --> 00:14:40,465
This is about the heart rate
of a healthy 16-year-old.

296
00:14:41,455 --> 00:14:44,504
What story is this data telling you?

297
00:14:45,475 --> 00:14:48,097
Obviously it's the data from someone

298
00:14:48,097 --> 00:14:51,136
who's made a drastic transformation,

299
00:14:51,136 --> 00:14:55,179
and fortunately for us,
that person happens to be here today.

300
00:14:56,150 --> 00:15:00,115
So that 350-pound guy that walked
into the emergency room with me

301
00:15:00,115 --> 00:15:03,665
is now an even sexier and healthier

302
00:15:03,665 --> 00:15:08,971
225-pound guy,
and that's his blood pressure trace.

303
00:15:10,293 --> 00:15:13,245
So over the course of that year and a half

304
00:15:13,245 --> 00:15:15,105
Donald's eating changed

305
00:15:15,105 --> 00:15:17,554
and our exercise regimen changed,

306
00:15:17,554 --> 00:15:19,671
and his heart rate responded,

307
00:15:19,671 --> 00:15:21,852
his blood pressure responded
to that change

308
00:15:21,852 --> 00:15:24,093
that he made in his body.

309
00:15:24,093 --> 00:15:25,507
So what's the take-home message

310
00:15:25,507 --> 00:15:28,587
that I want you to leave with today?

311
00:15:28,587 --> 00:15:33,808
By taking ownership of your data
just like we've done,

312
00:15:34,209 --> 00:15:37,533
just by taking this daily measurements
about yourself,

313
00:15:37,533 --> 00:15:40,021
you become the expert on your body.

314
00:15:40,021 --> 00:15:42,092
You become the authority.

315
00:15:42,092 --> 00:15:44,546
It's not hard to do.

316
00:15:44,546 --> 00:15:46,779
You don't have to have
a Ph.D. in statistics

317
00:15:46,779 --> 00:15:48,166
to be an expert in yourself.

318
00:15:48,166 --> 00:15:50,058
You don't have to have a medical degree

319
00:15:50,058 --> 00:15:52,219
to be your body's expert.

320
00:15:52,402 --> 00:15:55,482
Medical doctors,
they're experts on the population,

321
00:15:55,482 --> 00:15:58,593
but you are the expert on yourself.

322
00:15:58,593 --> 00:16:00,406
And so when two of you come together,

323
00:16:00,406 --> 00:16:02,432
when two experts come together,

324
00:16:02,432 --> 00:16:04,698
the two of you are able
to make a better decision

325
00:16:04,698 --> 00:16:07,125
than just your doctor alone.

326
00:16:07,125 --> 00:16:10,115
Now that you understand
the power of information

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00:16:10,115 --> 00:16:12,652
that you can get through
personal data collection,

328
00:16:12,652 --> 00:16:16,467
I'd like you all to stand
and raise your right hand.

329
00:16:16,467 --> 00:16:18,435
(Laughter)

330
00:16:18,435 --> 00:16:20,490
Yes, get it up.

331
00:16:24,217 --> 00:16:29,753
I challenge you to take ownership
of your data.

332
00:16:31,145 --> 00:16:34,334
And today, I hereby confer upon you

333
00:16:35,039 --> 00:16:38,466
a TEDx associate's degree
in elementary statistics

334
00:16:38,466 --> 00:16:42,995
with a concentration
in time-dependent data analysis

335
00:16:43,694 --> 00:16:47,566
with all the rights and privileges
appertaining thereto.

336
00:16:47,839 --> 00:16:51,258
And so the next time
you are in your doctor's office,

337
00:16:51,258 --> 00:16:54,248
as newly inducted statisticians,

338
00:16:54,297 --> 00:16:56,645
what should always be your response?

339
00:16:56,645 --> 00:16:59,642
Audience: Show me the data!
Talithia Williams: I can't hear you!

340
00:16:59,642 --> 00:17:00,965
Audience: Show me the data!

341
00:17:00,989 --> 00:17:02,120
TW: One more time!

342
00:17:02,120 --> 00:17:03,841
Audience: Show me the data!

343
00:17:03,841 --> 00:17:05,153
TW: Show me the data.

344
00:17:05,153 --> 00:17:06,119
Thank you.

345
00:17:06,119 --> 00:17:08,396
(Applause)